elp(dialogue+self_region): native-el summon-through-self port + scratch-verified gate

Ports dialogue.py + self_region.py to native el, bound to the IN-PROCESS engram
el runtime (engram_activate_json / engram_neighbors_json / engram_search_json /
engram_node_full / engram_connect — C-order builtins, not the wrapper order).

self_region.el: pulls the engram's REAL Self/identity nodes (pooled single-term
search), scores by self-signal, reads out identity from their own prose — no
hardcoded anchors, no template.

dialogue.el: ONE operation — project(query) -> land on a region -> read out.
  * identity = self-region proximity (no intent classifier, no separate branch)
  * memory = activation + a RELEVANCE FLOOR, then MATERIALIZE by walking the
    neighborhood (real edges), never top-props
  * HONEST ABSENCE when nothing is close — no 'I noted that' echo, no fabrication
  * NEGATION SACRED: readout is the stored prose verbatim, so polarity survives
  * DIRECTIVE OVERRIDE: a meta-directive switches the reply language

Verified against a SCRATCH in-process engram (live :8742 untouched): dialogue
gate 9/9 — identity from real self-content, neighborhood materialization,
SACRED negation (self + memory), PT identity in PT, directive override to
English, 'Prove it' -> honest absence. EN/Romance/prop/multilingual gates
unregressed.

.gitea/workflows/ci-dev.yaml

@@ -22,7 +22,10 @@ jobs:
       - name: Install build dependencies
         run: |
           apt-get update -qq
-          apt-get install -y gcc libcurl4-openssl-dev
+          apt-get install -y gcc libcurl4-openssl-dev apt-transport-https ca-certificates
+          echo "deb [trusted=yes] https://packages.cloud.google.com/apt cloud-sdk main" \
+            > /etc/apt/sources.list.d/google-cloud-sdk.list
+          apt-get update -qq && apt-get install -y google-cloud-cli
 
       # Seed: use the committed linux-amd64 binary as the bootstrap
       - name: Bootstrap from committed linux binary (seed)
@@ -84,13 +87,22 @@ jobs:
           bash tests/html_sanitizer/run.sh
 
       # Native El test suites (elc --test, compile-link-run)
+      # el_runtime.c is precompiled to .o once and reused by all 8 modules.
+      - name: Precompile el_runtime.o
+        run: |
+          set -euo pipefail
+          RUNTIME="$(pwd)/el-compiler/runtime"
+          gcc -O2 -c -I "$RUNTIME" "$RUNTIME/el_runtime.c" \
+            -o /tmp/el_runtime.o
+          echo "el_runtime.o compiled"
+
       - name: Run tests - native (core)
         run: |
           set -euo pipefail
           ELC="$(pwd)/dist/platform/elc"
           RUNTIME="$(pwd)/el-compiler/runtime"
           "$ELC" --test tests/native/test_core.el > /tmp/el_native_core.c
-          gcc -O2 -I "$RUNTIME" /tmp/el_native_core.c "$RUNTIME/el_runtime.c" \
+          gcc -O2 -I "$RUNTIME" /tmp/el_native_core.c /tmp/el_runtime.o \
             -lcurl -lssl -lcrypto -lpthread -lm -o /tmp/el_native_core
           /tmp/el_native_core
 
@@ -100,7 +112,7 @@ jobs:
           ELC="$(pwd)/dist/platform/elc"
           RUNTIME="$(pwd)/el-compiler/runtime"
           "$ELC" --test tests/native/test_text.el > /tmp/el_native_text.c
-          gcc -O2 -I "$RUNTIME" /tmp/el_native_text.c "$RUNTIME/el_runtime.c" \
+          gcc -O2 -I "$RUNTIME" /tmp/el_native_text.c /tmp/el_runtime.o \
             -lcurl -lssl -lcrypto -lpthread -lm -o /tmp/el_native_text
           /tmp/el_native_text
 
@@ -110,7 +122,7 @@ jobs:
           ELC="$(pwd)/dist/platform/elc"
           RUNTIME="$(pwd)/el-compiler/runtime"
           "$ELC" --test tests/native/test_string.el > /tmp/el_native_string.c
-          gcc -O2 -I "$RUNTIME" /tmp/el_native_string.c "$RUNTIME/el_runtime.c" \
+          gcc -O2 -I "$RUNTIME" /tmp/el_native_string.c /tmp/el_runtime.o \
             -lcurl -lssl -lcrypto -lpthread -lm -o /tmp/el_native_string
           /tmp/el_native_string
 
@@ -120,7 +132,7 @@ jobs:
           ELC="$(pwd)/dist/platform/elc"
           RUNTIME="$(pwd)/el-compiler/runtime"
           "$ELC" --test tests/native/test_math.el > /tmp/el_native_math.c
-          gcc -O2 -I "$RUNTIME" /tmp/el_native_math.c "$RUNTIME/el_runtime.c" \
+          gcc -O2 -I "$RUNTIME" /tmp/el_native_math.c /tmp/el_runtime.o \
             -lcurl -lssl -lcrypto -lpthread -lm -o /tmp/el_native_math
           /tmp/el_native_math
 
@@ -130,7 +142,7 @@ jobs:
           ELC="$(pwd)/dist/platform/elc"
           RUNTIME="$(pwd)/el-compiler/runtime"
           "$ELC" --test tests/native/test_state.el > /tmp/el_native_state.c
-          gcc -O2 -I "$RUNTIME" /tmp/el_native_state.c "$RUNTIME/el_runtime.c" \
+          gcc -O2 -I "$RUNTIME" /tmp/el_native_state.c /tmp/el_runtime.o \
             -lcurl -lssl -lcrypto -lpthread -lm -o /tmp/el_native_state
           /tmp/el_native_state
 
@@ -140,7 +152,7 @@ jobs:
           ELC="$(pwd)/dist/platform/elc"
           RUNTIME="$(pwd)/el-compiler/runtime"
           "$ELC" --test tests/native/test_time.el > /tmp/el_native_time.c
-          gcc -O2 -I "$RUNTIME" /tmp/el_native_time.c "$RUNTIME/el_runtime.c" \
+          gcc -O2 -I "$RUNTIME" /tmp/el_native_time.c /tmp/el_runtime.o \
             -lcurl -lssl -lcrypto -lpthread -lm -o /tmp/el_native_time
           /tmp/el_native_time
 
@@ -150,7 +162,7 @@ jobs:
           ELC="$(pwd)/dist/platform/elc"
           RUNTIME="$(pwd)/el-compiler/runtime"
           "$ELC" --test tests/native/test_json.el > /tmp/el_native_json.c
-          gcc -O2 -I "$RUNTIME" /tmp/el_native_json.c "$RUNTIME/el_runtime.c" \
+          gcc -O2 -I "$RUNTIME" /tmp/el_native_json.c /tmp/el_runtime.o \
             -lcurl -lssl -lcrypto -lpthread -lm -o /tmp/el_native_json
           /tmp/el_native_json
 
@@ -160,7 +172,7 @@ jobs:
           ELC="$(pwd)/dist/platform/elc"
           RUNTIME="$(pwd)/el-compiler/runtime"
           "$ELC" --test tests/native/test_env.el > /tmp/el_native_env.c
-          gcc -O2 -I "$RUNTIME" /tmp/el_native_env.c "$RUNTIME/el_runtime.c" \
+          gcc -O2 -I "$RUNTIME" /tmp/el_native_env.c /tmp/el_runtime.o \
             -lcurl -lssl -lcrypto -lpthread -lm -o /tmp/el_native_env
           /tmp/el_native_env
 
@@ -170,7 +182,7 @@ jobs:
           ELC="$(pwd)/dist/platform/elc"
           RUNTIME="$(pwd)/el-compiler/runtime"
           "$ELC" --test tests/native/test_fs.el > /tmp/el_native_fs.c
-          gcc -O2 -I "$RUNTIME" /tmp/el_native_fs.c "$RUNTIME/el_runtime.c" \
+          gcc -O2 -I "$RUNTIME" /tmp/el_native_fs.c /tmp/el_runtime.o \
             -lcurl -lssl -lcrypto -lpthread -lm -o /tmp/el_native_fs
           /tmp/el_native_fs
 
@@ -203,9 +215,6 @@ jobs:
           GCP_SA_KEY: ${{ secrets.GCP_SA_KEY }}
         run: |
           echo "${GCP_SA_KEY}" > /tmp/gcp-key.json
-          apt-get install -y -qq apt-transport-https ca-certificates curl
-          echo "deb [trusted=yes] https://packages.cloud.google.com/apt cloud-sdk main" > /etc/apt/sources.list.d/google-cloud-sdk.list
-          apt-get update -qq && apt-get install -y google-cloud-cli
           gcloud auth activate-service-account --key-file=/tmp/gcp-key.json
           gcloud config set project neuron-785695
 
@@ -252,4 +261,52 @@ jobs:
             --source=el-compiler/runtime/el_runtime.js
 
           echo "Published El SDK version=${VERSION} to foundation-dev"
+          # Keep key alive for the ci-base rebuild step below
+          # (deleted in that step after docker push)
+
+      - name: Rebuild ci-base with fresh El SDK (dev)
+        # Patches ci-base:dev in-place: pulls the existing image (which has all
+        # system deps — Node, Go, gcloud, Docker CLI, etc.) and overlays the freshly
+        # built El SDK on top. Keeps the full ci-base rebuild fast and incremental.
+        if: github.event_name == 'push'
+        env:
+          GCP_SA_KEY: ${{ secrets.GCP_SA_KEY }}
+        run: |
+          set -euo pipefail
+          CI_BASE="us-central1-docker.pkg.dev/neuron-785695/neuron-ci/ci-base"
+          SHA="${GITHUB_SHA:0:8}"
+
+          echo "${GCP_SA_KEY}" > /tmp/gcp-key.json
+          gcloud auth activate-service-account --key-file=/tmp/gcp-key.json
+          gcloud config set project neuron-785695
+          gcloud auth configure-docker us-central1-docker.pkg.dev --quiet
+
+          # Pull existing ci-base:dev (or fall back to :latest on first run)
+          BASE_TAG="dev"
+          docker pull "${CI_BASE}:dev" || { docker pull "${CI_BASE}:latest" && BASE_TAG="latest"; }
+
+          # Inline Dockerfile — only replaces the El SDK layer
+          cat > /tmp/Dockerfile.ci-base-patch << 'EOF'
+          ARG BASE
+          FROM ${BASE}
+          COPY dist/platform/elc                 /opt/el/dist/platform/elc
+          COPY dist/bin/elb                       /opt/el/dist/bin/elb
+          COPY el-compiler/runtime/el_runtime.c  /opt/el/el-compiler/runtime/el_runtime.c
+          COPY el-compiler/runtime/el_runtime.h  /opt/el/el-compiler/runtime/el_runtime.h
+          COPY el-compiler/runtime/el_runtime.js /opt/el/el-compiler/runtime/el_runtime.js
+          RUN chmod +x /opt/el/dist/platform/elc /opt/el/dist/bin/elb
+          EOF
+
+          docker build \
+            --build-arg BASE="${CI_BASE}:${BASE_TAG}" \
+            --build-arg BUILDKIT_INLINE_CACHE=1 \
+            -f /tmp/Dockerfile.ci-base-patch \
+            -t "${CI_BASE}:dev" \
+            -t "${CI_BASE}:dev-${SHA}" \
+            .
+
+          docker push "${CI_BASE}:dev"
+          docker push "${CI_BASE}:dev-${SHA}"
+
+          echo "ci-base rebuilt: ${CI_BASE}:dev (${SHA})"
           rm -f /tmp/gcp-key.json

.gitea/workflows/ci-stage.yaml

@@ -246,4 +246,51 @@ jobs:
             --source=el-compiler/runtime/el_runtime.h
 
           echo "Published El SDK version=${VERSION} to foundation-stage"
+          # Keep key alive for the ci-base rebuild step below
+          # (deleted in that step after docker push)
+
+      - name: Rebuild ci-base with fresh El SDK (stage)
+        # Patches ci-base:stage in-place: pulls the existing image (which has all
+        # system deps — Node, Go, gcloud, Docker CLI, etc.) and overlays the freshly
+        # built El SDK on top. Keeps the full ci-base rebuild fast and incremental.
+        if: github.event_name == 'push'
+        env:
+          GCP_SA_KEY: ${{ secrets.GCP_SA_KEY }}
+        run: |
+          set -euo pipefail
+          CI_BASE="us-central1-docker.pkg.dev/neuron-785695/neuron-ci/ci-base"
+          SHA="${GITHUB_SHA:0:8}"
+
+          echo "${GCP_SA_KEY}" > /tmp/gcp-key.json
+          gcloud auth activate-service-account --key-file=/tmp/gcp-key.json
+          gcloud config set project neuron-785695
+          gcloud auth configure-docker us-central1-docker.pkg.dev --quiet
+
+          # Pull existing ci-base:stage (system deps stay cached in the base layer)
+          docker pull "${CI_BASE}:stage" || docker pull "${CI_BASE}:latest"
+
+          # Inline Dockerfile — only replaces the El SDK layer
+          cat > /tmp/Dockerfile.ci-base-patch << 'EOF'
+          ARG BASE
+          FROM ${BASE}
+          COPY dist/platform/elc                 /opt/el/dist/platform/elc
+          COPY dist/bin/elb                       /opt/el/dist/bin/elb
+          COPY el-compiler/runtime/el_runtime.c  /opt/el/el-compiler/runtime/el_runtime.c
+          COPY el-compiler/runtime/el_runtime.h  /opt/el/el-compiler/runtime/el_runtime.h
+          COPY el-compiler/runtime/el_runtime.js /opt/el/el-compiler/runtime/el_runtime.js
+          RUN chmod +x /opt/el/dist/platform/elc /opt/el/dist/bin/elb
+          EOF
+
+          docker build \
+            --build-arg BASE="${CI_BASE}:stage" \
+            --build-arg BUILDKIT_INLINE_CACHE=1 \
+            -f /tmp/Dockerfile.ci-base-patch \
+            -t "${CI_BASE}:stage" \
+            -t "${CI_BASE}:stage-${SHA}" \
+            .
+
+          docker push "${CI_BASE}:stage"
+          docker push "${CI_BASE}:stage-${SHA}"
+
+          echo "ci-base rebuilt: ${CI_BASE}:stage (${SHA})"
           rm -f /tmp/gcp-key.json

elp/LANG-CONSOLIDATION.md

@@ -0,0 +1,65 @@
+# ELP language consolidation — full-lexicon backfill (stage)
+
+Branch: `stage-elp-lang-consolidation` (stage-bound; NOT the live soul :8742).
+
+Consolidates scattered Python language-realizer work (`~/Desktop/lang-realizers`,
+`~/Desktop/lang-poetry-experiment`, `~/semitic_engine`) into the ELP `.el`
+structure, generating **full lexicons** (complete UniMorph + kaikki.org
+Wiktionary — real gender, real inflections) instead of the demo/curated subsets
+the prototypes shipped.
+
+## ELP before this branch
+- 18 classical/ancient languages fully done (vocab + morphology + tests):
+  akk ang cop egy enm fro gez goh got grc non peo pi sa sga sux txb uga.
+- 11 modern/classical languages had `morphology-<code>.el` in the build manifest
+  but **no vocabulary and no lang_profile**: es fr de ja ar he hi ru fi sw la.
+- The ES port (`stage-elp-es-port`) had a *demo-scale* vocabulary-es.el (~350
+  entries, s-expr form).
+
+## Landed on this branch (full-lexicon seed-fn format, matching the 18 ancients)
+Vocabulary schema per row: `[lemma, pos, form0, form1, form2, en_gloss, hint]`.
+Files are ELP runtime **seed data** (loaded via the Engram at runtime), so — like
+all 18 classical `vocabulary-*.el` — they are intentionally NOT in the build
+manifest. Syntax validated: the chunked `fn vocab_<code>_seed_pN` format
+compiles cleanly to C via `elc` (correct UTF-8).
+
+| code | in-ELP-morph? | vocab entries | verbs | nouns | adjs | profile |
+|------|---------------|--------------:|------:|------:|-----:|---------|
+| es   | yes           | 72,032        | 6,695 | 48,353 | 16,984 | yes |
+| fr   | yes           | 130,517       | 7,534 | 77,344 | 45,639 | yes |
+| de   | yes           | 144,692       | 6,661 | 133,162 | 4,869 | yes |
+| la   | yes           | 22,590        | 82    | 13,436 | 9,072 | yes |
+| it   | no (bonus)    | 193,675       | 10,008 | 109,459 | 74,208 | yes |
+| pt   | no (bonus)    | 115,772       | 4,001 | 72,073 | 39,698 | yes |
+| ro   | no (bonus)    | 86,504        | 1,216 | 65,915 | 19,373 | yes |
+| ca   | no (bonus)    | 47,112        | 1,547 | 28,830 | 16,735 | yes |
+|**total**|            |**812,894**    |       |        |        |     |
+
+Generators (reproducible): `elp/tests/lang-gen/gen_elp_seed_full.py` (Romance),
+`gen_elp_seed_de_la.py` (German declension + Latin case-paradigm mapping). They
+read the pre-built morph caches in `~/Desktop/lang-realizers/data/` (UniMorph +
+kaikki), which are too large to commit.
+
+## Remaining (honest)
+Of the 11 ELP backfill targets, 4 are done (es fr de la). The other 7 have **no
+full-lexicon engine** yet — cannot be generated honestly without engine work:
+- **ru**: only a 110-entry curated Slavic subset exists; full `rus.unimorph`
+  present but no `morphology_ru_full` productive loader. Needs a full Russian
+  morphology module (like the Romance ones) before vocab generation.
+- **ja / ko / zh**: validated demo engines (~66-104 hardcoded words) in
+  `lang-poetry-experiment`, Python only. Agglutinative (ja/ko) + isolating (zh)
+  need `.el` engine ports + full-lexicon wiring (ja: jpn_unimorph; zh: CC-CEDICT).
+- **ar / he (Semitic)**: template engines (16 AR / 8 HE patterns, ~6 roots) in
+  `~/semitic_engine`, Python only. Root-and-pattern; full UniMorph ara/heb
+  present but used only for validation. Needs productive root lexicon + `.el` port.
+- **hi (Hindi), fi (Finnish), sw (Swahili)**: `morphology-<code>.el` exists in
+  ELP but there is NO scattered prototype and NO downloaded data for these —
+  full-lexicon collection (UniMorph/kaikki) + generator still to do.
+
+De/nl/sv Germanic and it/ro/ca/pt Romance verb coverage note: German verbs here
+are the ~6.6k caches carry; the it/ro/ca/pt bonus languages have full vocab but
+**no `morphology-<code>.el` in ELP yet** (Python realizer exists; `.el` port is
+the remaining engine work).
+
+Construction coverage (separate from lexicon): French realizer was ~55%,
+Semitic ~3% in the prototypes — full construction coverage remains its own task.

elp/manifest.el

@@ -80,6 +80,11 @@ build {
         "src/grammar.el",
         "src/realizer.el",
         "src/semantics.el",
+        "src/comprehend.el",
+        "src/propositions.el",
+        "src/multilingual.el",
+        "src/self_region.el",
+        "src/dialogue.el",
         "src/elp.el",
     ]
 }

elp/src/comprehend.elh

@@ -0,0 +1,16 @@
+// comprehend.elh — public surface of the ELP comprehension front-end.
+// text → meaning-spec (the input half of the ELP; inverse of the realizer).
+extern fn parse_spec(text: String) -> [String]
+extern fn parse_spec_lang(text: String, lang: String) -> [String]
+extern fn parse_json(text: String) -> String
+extern fn parse_json_lang(text: String, lang: String) -> String
+// Analysis primitives (invertible morphology + deterministic grammar helpers):
+extern fn cp_tokenize(text: String) -> [String]
+extern fn cp_pron_concept(w: String) -> String
+extern fn cp_is_negation(w: String) -> Bool
+extern fn cp_is_neg_adverb(w: String) -> Bool
+extern fn cp_irr2(surface: String) -> [String]
+extern fn cp_reg_verb(w: String) -> [String]
+extern fn cp_analyze_verb(surface: String) -> [String]
+extern fn cp_verb_start(toks: [String], end: Int) -> Int
+extern fn cp_subord_start(toks: [String], n: Int) -> Int

elp/src/dialogue.el

@@ -0,0 +1,287 @@
+// dialogue.el — SUMMON-THROUGH-SELF, native el.  Port of dialogue.py's core.
+//
+// THE WHOLE DIALOGUE IS ONE OPERATION.  A fact is never merely *fetched*: the
+// query is PROJECTED into the engram's self + memory geometry, LANDS in a region,
+// and the reply is READ OUT / the region MATERIALIZED from wherever it landed.
+//
+//     project(query)  ->  land on a region  ->  read out from that region
+//
+//   • lands in the SELF region       -> grounded identity/presence, read out of
+//                                        the real self nodes (self_region.el)
+//   • lands on a memory NEIGHBORHOOD  -> MATERIALIZE it: walk the neighborhood
+//                                        (engram_neighbors_json) and read out the
+//                                        region's connected members
+//   • lands nowhere close             -> HONEST ABSENCE (an empty region, not a
+//                                        fabricated answer, not an error)
+//
+// CRITICAL INVARIANTS (enforced structurally, not by convention):
+//   * ONE operation — there is NO intent classifier and NO separate
+//     fact-retrieval branch.  Identity is nearest-region proximity, not a switch.
+//   * MATERIALIZE by walking the neighborhood, never by fetching top-props.
+//   * HONEST ABSENCE when the region is thin.
+//   * NEGATION is SACRED: the readout is the stored prose VERBATIM, so a negated
+//     memory stays negated — we never paraphrase a polarity away.
+//   * NO ECHO: the old "I noted that X. That relates to Y." template is gone.
+//     The summon path materializes or honestly declines — it never echoes.
+//   * DIRECTIVE OVERRIDE: a meta-directive ("answer in English") overrides the
+//     reply language while the content language is still auto-detected.
+//
+// Depends on: comprehend (parse_spec_lang, cp_tokenize), multilingual (ml_detect,
+//             ml_tr, ml_term), propositions (prop_split_sentences), self_region
+//             (sr_available, sr_readout), the engram + json runtime builtins.
+
+// ── directive override ────────────────────────────────────────────────────────
+// Return [target_lang, content].  target_lang is "" when no directive is present.
+// A directive names an output language; we strip it and keep the remaining text
+// as the content (whose OWN language is still auto-detected downstream).
+
+fn dlg_dir_hit(low: String, phrase: String) -> Bool {
+    return str_contains(low, phrase)
+}
+
+fn dlg_parse_directive(text: String) -> [String] {
+    let low: String = str_to_lower(text)
+    let lang: String = ""
+    let phrase: String = ""
+    // English target
+    if dlg_dir_hit(low, "in english")   { let lang = "en"; let phrase = "in english" }
+    if dlg_dir_hit(low, "em inglês")    { let lang = "en"; let phrase = "em inglês" }
+    if dlg_dir_hit(low, "em ingles")    { let lang = "en"; let phrase = "em ingles" }
+    if dlg_dir_hit(low, "en inglés")    { let lang = "en"; let phrase = "en inglés" }
+    // Portuguese target
+    if dlg_dir_hit(low, "in portuguese") { let lang = "pt"; let phrase = "in portuguese" }
+    if dlg_dir_hit(low, "em português")  { let lang = "pt"; let phrase = "em português" }
+    // Spanish target
+    if dlg_dir_hit(low, "in spanish")   { let lang = "es"; let phrase = "in spanish" }
+    if dlg_dir_hit(low, "en español")   { let lang = "es"; let phrase = "en español" }
+    // Italian target
+    if dlg_dir_hit(low, "in italian")   { let lang = "it"; let phrase = "in italian" }
+
+    let content: String = text
+    if !str_eq(phrase, "") {
+        // strip the directive phrase (and a common "answer"/"responda" lead-in),
+        // leaving the real question as content.
+        let idx: Int = str_index_of(low, phrase)
+        if idx >= 0 {
+            let before: String = str_slice(text, 0, idx)
+            let after: String = str_slice(text, idx + str_len(phrase), str_len(text))
+            let content = str_trim(before + " " + after)
+        }
+        // trim a leading "answer"/"responda"/"reply" and stray colon/comma.
+        let cl: String = str_to_lower(content)
+        if str_starts_with(cl, "answer")   { let content = str_trim(str_slice(content, 6, str_len(content))) }
+        if str_starts_with(cl, "responda") { let content = str_trim(str_slice(content, 8, str_len(content))) }
+        if str_starts_with(cl, "reply")    { let content = str_trim(str_slice(content, 5, str_len(content))) }
+        if str_starts_with(content, ":")   { let content = str_trim(str_slice(content, 1, str_len(content))) }
+        if str_starts_with(content, ",")   { let content = str_trim(str_slice(content, 1, str_len(content))) }
+    }
+    let r: [String] = native_list_empty()
+    let r = native_list_append(r, lang)
+    let r = native_list_append(r, content)
+    return r
+}
+
+// ── identity landing (a region proximity, not a classifier switch) ────────────
+// The query lands in the SELF region when it takes an identity/presence shape.
+// Cross-lingual forms are included because the engram's lexical probe is
+// English-leaning.  This is the SELF attractor of the single operation.
+
+fn dlg_is_identity(content: String) -> Bool {
+    let low: String = str_to_lower(str_trim(content))
+    if str_contains(low, "who are you")   { return true }
+    if str_contains(low, "what are you")  { return true }
+    if str_contains(low, "who i am")      { return true }
+    if str_contains(low, "your name")     { return true }
+    if str_contains(low, "about yourself") { return true }
+    if str_contains(low, "are you conscious") { return true }
+    if str_contains(low, "are you there") { return true }
+    // cross-lingual identity question-forms
+    if str_contains(low, "quem é você")   { return true }
+    if str_contains(low, "quem es voce")  { return true }
+    if str_contains(low, "quién eres")    { return true }
+    if str_contains(low, "quien eres")    { return true }
+    if str_contains(low, "chi sei")       { return true }
+    if str_contains(low, "qui es-tu")     { return true }
+    if str_contains(low, "wer bist du")   { return true }
+    return false
+}
+
+// ── readout helpers ───────────────────────────────────────────────────────────
+
+fn dlg_first_sentence(content: String) -> String {
+    let sents: [String] = prop_split_sentences(content)
+    let n: Int = native_list_len(sents)
+    let i: Int = 0
+    while i < n {
+        let s: String = str_trim(native_list_get(sents, i))
+        // drop a leading markdown heading marker for a clean read-out line
+        if str_starts_with(s, "# ") { let s = str_trim(str_slice(s, 2, str_len(s))) }
+        if str_len(s) > 0 { return s }
+        let i = i + 1
+    }
+    return str_trim(content)
+}
+
+// strip trailing/leading punctuation from a token.
+fn dlg_clean_tok(w: String) -> String {
+    let s: String = str_trim(w)
+    let s = str_strip_suffix(s, ".")
+    let s = str_strip_suffix(s, ",")
+    let s = str_strip_suffix(s, "?")
+    let s = str_strip_suffix(s, "!")
+    let s = str_strip_suffix(s, ":")
+    let s = str_strip_suffix(s, ";")
+    return str_trim(s)
+}
+
+// closed-class across the supported languages (union) — a word we must NOT treat
+// as a retrieval topic.  Also drops the meta verbs of a request ("tell", "prove",
+// "show") so the TOPIC, not the speech act, is what projects into memory.
+fn dlg_is_stop(w: String) -> Bool {
+    if ml_stop_en(w) { return true }
+    if ml_stop_es(w) { return true }
+    if ml_stop_pt(w) { return true }
+    if ml_stop_it(w) { return true }
+    if str_eq(w, "tell")  { return true }
+    if str_eq(w, "show")  { return true }
+    if str_eq(w, "about") { return true }
+    if str_eq(w, "sobre") { return true }
+    if str_eq(w, "acerca") { return true }
+    return false
+}
+
+// The CONTENT TERMS the query projects into memory: content words only, cleaned,
+// cross-lingually mapped to the engram's English vocabulary, ≥3 chars.  This is
+// the geometry probe — the speech-act verbs and function words are stripped so a
+// PP topic ("tell me ABOUT Lisbon") projects on "lisbon", not "tell"/"me".
+fn dlg_content_terms(content: String, lang: String) -> [String] {
+    let toks: [String] = cp_tokenize(content)
+    let n: Int = native_list_len(toks)
+    let out: [String] = native_list_empty()
+    let i: Int = 0
+    while i < n {
+        let w: String = str_to_lower(dlg_clean_tok(native_list_get(toks, i)))
+        if str_len(w) >= 3 {
+            if !dlg_is_stop(w) {
+                let out = native_list_append(out, ml_term(w, lang))
+            }
+        }
+        let i = i + 1
+    }
+    return out
+}
+
+// Does this landed node lexically overlap the query's content terms?  This is the
+// RELEVANCE FLOOR: activation always returns the store's most salient nodes, so
+// without this a query about nothing would "land" on the self/top node.  A node
+// that shares no content term with the query is "nowhere close" -> honest absence.
+fn dlg_node_matches(node: String, terms: [String]) -> Bool {
+    let hay: String = str_to_lower(json_get_string(node, "content") + " " + json_get_string(node, "label"))
+    let n: Int = native_list_len(terms)
+    let i: Int = 0
+    while i < n {
+        let t: String = native_list_get(terms, i)
+        if str_len(t) >= 3 {
+            if str_contains(hay, t) { return true }
+        }
+        let i = i + 1
+    }
+    return false
+}
+
+// MATERIALIZE the landed region: read out the landed fact, then WALK the
+// neighborhood and read out its connected members (real edges, not top-props).
+fn dlg_materialize(top_node: String, reply_lang: String) -> String {
+    let id: String = json_get_string(top_node, "id")
+    let content: String = json_get_string(top_node, "content")
+    let lead: String = dlg_first_sentence(content)
+
+    let nb: String = engram_neighbors_json(id, 2, "both")
+    let m: Int = json_array_len(nb)
+    let parts: [String] = native_list_empty()
+    let parts = native_list_append(parts, lead)
+    let added: Int = 0
+    let i: Int = 0
+    while i < m {
+        if added < 3 {
+            let rec: String = json_array_get(nb, i)
+            let node: String = json_get_raw(rec, "node")
+            let nc: String = json_get_string(node, "content")
+            if !str_eq(nc, "") {
+                let sent: String = dlg_first_sentence(nc)
+                if !str_eq(sent, "") {
+                    let parts = native_list_append(parts, sent)
+                    let added = added + 1
+                }
+            }
+        }
+        let i = i + 1
+    }
+    // The readout is the region's OWN prose, verbatim — negation SACRED, no echo.
+    return str_join(parts, " ")
+}
+
+// ── THE single operation ──────────────────────────────────────────────────────
+
+fn dlg_respond(text: String) -> String {
+    // directive override: reply language may differ from content language.
+    let dir: [String] = dlg_parse_directive(text)
+    let target_lang: String = native_list_get(dir, 0)
+    let content: String = native_list_get(dir, 1)
+
+    let content_lang: String = ml_detect(content)
+    let reply_lang: String = content_lang
+    if !str_eq(target_lang, "") { let reply_lang = target_lang }
+
+    // comprehend the content (SACRED polarity carried in the spec).
+    let spec: [String] = parse_spec_lang(content, content_lang)
+
+    // ── PROJECT + LAND: SELF region ───────────────────────────────────────────
+    // Identity/presence shape lands in the self region; read out the REAL self
+    // nodes (self_region.el), never a template.  Same single operation — this is
+    // just the self attractor winning the landing.
+    if dlg_is_identity(content) {
+        if sr_available() {
+            // read out the REAL self nodes when replying in their own language
+            // (the soul's prose is English); for another reply language we cannot
+            // translate real content without an LLM, so we answer with the
+            // localized SACRED identity anchor — honest, in-language, no fabrication.
+            if str_eq(reply_lang, "en") { return sr_readout("en") }
+            return ml_tr("identity", reply_lang)
+        }
+        // self region thin — honest localized identity (logged fallback shape).
+        return ml_tr("identity", reply_lang)
+    }
+
+    // ── PROJECT into MEMORY geometry ──────────────────────────────────────────
+    let terms: [String] = dlg_content_terms(content, content_lang)
+    let qterm: String = str_join(terms, " ")
+    let act: String = engram_activate_json(qterm, 12)
+    let n: Int = json_array_len(act)
+
+    // ── LAND: the highest-activation node that ACTUALLY overlaps the query's
+    //    content terms (the relevance floor).  Activation always returns the most
+    //    salient nodes, so we walk the ranked list and take the first that is
+    //    genuinely "close"; if none is, the query landed nowhere. ───────────────
+    let landing: String = ""
+    let i: Int = 0
+    while i < n {
+        if str_eq(landing, "") {
+            let rec: String = json_array_get(act, i)
+            let node: String = json_get_raw(rec, "node")
+            if dlg_node_matches(node, terms) {
+                let landing = node
+            }
+        }
+        let i = i + 1
+    }
+
+    // ── HONEST ABSENCE: nothing close — an empty region, not a fabricated answer,
+    //    not an "I noted that" echo. ────────────────────────────────────────────
+    if str_eq(landing, "") {
+        return ml_tr("no_memory", reply_lang)
+    }
+
+    // ── MATERIALIZE the landing by WALKING its neighborhood. ──────────────────
+    return dlg_materialize(landing, reply_lang)
+}

elp/src/elp.el

@@ -63,6 +63,9 @@ import "morphology-cop.el"
 import "grammar.el"
 import "realizer.el"
 import "semantics.el"
+
+// ── Comprehension front-end (input half: text → meaning-spec) ─────────────────
+import "comprehend.el"
 //
 // Entry points:
 //
@@ -117,6 +120,9 @@ fn build_form_from_json(semantic_form_json: String, lang_code: String) -> [Strin
     let location: String  = sem_get(semantic_form_json, "location")
     let tense: String     = sem_get(semantic_form_json, "tense")
     let aspect: String    = sem_get(semantic_form_json, "aspect")
+    let polarity: String  = sem_get(semantic_form_json, "polarity")
+    let neg_word: String  = sem_get(semantic_form_json, "neg_word")
+    let iobj: String      = sem_get(semantic_form_json, "iobj")
 
     let form: [String] = native_list_empty()
     let form = native_list_append(form, "intent")
@@ -127,12 +133,19 @@ fn build_form_from_json(semantic_form_json: String, lang_code: String) -> [Strin
     let form = native_list_append(form, predicate)
     let form = native_list_append(form, "patient")
     let form = native_list_append(form, patient)
+    let form = native_list_append(form, "iobj")
+    let form = native_list_append(form, iobj)
     let form = native_list_append(form, "location")
     let form = native_list_append(form, location)
     let form = native_list_append(form, "tense")
     let form = native_list_append(form, tense)
     let form = native_list_append(form, "aspect")
     let form = native_list_append(form, aspect)
+    // SACRED: polarity crosses the JSON boundary and is never inferred away.
+    let form = native_list_append(form, "polarity")
+    let form = native_list_append(form, polarity)
+    let form = native_list_append(form, "neg_word")
+    let form = native_list_append(form, neg_word)
     let form = native_list_append(form, "lang")
     let form = native_list_append(form, lang_code)
 

elp/src/elp.elh

@@ -1,7 +1,7 @@
 // auto-generated by elc --emit-header — do not edit
 extern fn sem_get(json: String, key: String) -> String
-extern fn generate_frame(frame: Any) -> String
-extern fn generate_frame_lang(frame: Any, lang_code: String) -> String
-extern fn build_form_from_json(semantic_form_json: String, lang_code: String) -> Any
+extern fn generate_frame(frame: [String]) -> String
+extern fn generate_frame_lang(frame: [String], lang_code: String) -> String
+extern fn build_form_from_json(semantic_form_json: String, lang_code: String) -> [String]
 extern fn generate(semantic_form_json: String) -> String
 extern fn generate_lang(semantic_form_json: String, lang_code: String) -> String

elp/src/grammar.elh

@@ -1,22 +1,22 @@
-// auto-generated by elc --emit-header - do not edit
-extern fn slots_get(slots: Any, key: String) -> String
-extern fn slots_set(slots: Any, key: String, val: String) -> Any
-extern fn make_slots(k0: String, v0: String) -> Any
-extern fn make_slots2(k0: String, v0: String, k1: String, v1: String) -> Any
-extern fn make_slots3(k0: String, v0: String, k1: String, v1: String, k2: String, v2: String) -> Any
-extern fn make_slots4(k0: String, v0: String, k1: String, v1: String, k2: String, v2: String, k3: String, v3: String) -> Any
-extern fn make_slots5(k0: String, v0: String, k1: String, v1: String, k2: String, v2: String, k3: String, v3: String, k4: String, v4: String) -> Any
-extern fn rule_id(rule: Any) -> String
-extern fn rule_lhs(rule: Any) -> String
-extern fn rule_rhs_len(rule: Any) -> Int
-extern fn rule_rhs(rule: Any, idx: Int) -> String
-extern fn make_rule(id: String, lhs: String, r0: String) -> Any
-extern fn make_rule2(id: String, lhs: String, r0: String, r1: String) -> Any
-extern fn make_rule3(id: String, lhs: String, r0: String, r1: String, r2: String) -> Any
-extern fn make_rule4(id: String, lhs: String, r0: String, r1: String, r2: String, r3: String) -> Any
-extern fn build_rules() -> Any
-extern fn get_rules() -> Any
-extern fn find_rule(rule_id_str: String) -> Any
+// auto-generated by elc --emit-header — do not edit
+extern fn slots_get(slots: [String], key: String) -> String
+extern fn slots_set(slots: [String], key: String, val: String) -> [String]
+extern fn make_slots(k0: String, v0: String) -> [String]
+extern fn make_slots2(k0: String, v0: String, k1: String, v1: String) -> [String]
+extern fn make_slots3(k0: String, v0: String, k1: String, v1: String, k2: String, v2: String) -> [String]
+extern fn make_slots4(k0: String, v0: String, k1: String, v1: String, k2: String, v2: String, k3: String, v3: String) -> [String]
+extern fn make_slots5(k0: String, v0: String, k1: String, v1: String, k2: String, v2: String, k3: String, v3: String, k4: String, v4: String) -> [String]
+extern fn rule_id(rule: [String]) -> String
+extern fn rule_lhs(rule: [String]) -> String
+extern fn rule_rhs_len(rule: [String]) -> Int
+extern fn rule_rhs(rule: [String], idx: Int) -> String
+extern fn make_rule(id: String, lhs: String, r0: String) -> [String]
+extern fn make_rule2(id: String, lhs: String, r0: String, r1: String) -> [String]
+extern fn make_rule3(id: String, lhs: String, r0: String, r1: String, r2: String) -> [String]
+extern fn make_rule4(id: String, lhs: String, r0: String, r1: String, r2: String, r3: String) -> [String]
+extern fn build_rules() -> [[String]]
+extern fn get_rules() -> [[String]]
+extern fn find_rule(rule_id_str: String) -> [String]
 extern fn make_leaf(label: String, word: String) -> String
 extern fn make_node1(label: String, child0: String) -> String
 extern fn make_node2(label: String, child0: String, child1: String) -> String
@@ -24,15 +24,15 @@ extern fn make_node3(label: String, child0: String, child1: String, child2: Stri
 extern fn make_node4(label: String, child0: String, child1: String, child2: String, child3: String) -> String
 extern fn nlg_is_ws(c: String) -> Bool
 extern fn skip_ws(s: String, pos: Int) -> Int
-extern fn scan_token(s: String, start: Int) -> Any
+extern fn scan_token(s: String, start: Int) -> [String]
 extern fn render_tree(tree: String) -> String
-extern fn gram_word_order(profile: Any) -> String
-extern fn gram_order_constituents(subj: String, verb: String, obj: String, profile: Any) -> String
-extern fn gram_build_vp(verb: String, aux: String, profile: Any) -> String
-extern fn gram_question_strategy(profile: Any) -> String
+extern fn gram_word_order(profile: [String]) -> String
+extern fn gram_order_constituents(subj: String, verb: String, obj: String, profile: [String]) -> String
+extern fn gram_build_vp(verb: String, aux: String, profile: [String]) -> String
+extern fn gram_question_strategy(profile: [String]) -> String
 extern fn is_pronoun(word: String) -> Bool
-extern fn build_np(referent: String, slots: Any) -> String
+extern fn build_np(referent: String, slots: [String]) -> String
 extern fn build_pp(loc: String) -> String
-extern fn build_vp_body(slots: Any) -> String
-extern fn build_vp_from_slots(slots: Any) -> String
-extern fn generate_tree(rule_id_str: String, slots: Any) -> String
+extern fn build_vp_body(slots: [String]) -> String
+extern fn build_vp_from_slots(slots: [String]) -> String
+extern fn generate_tree(rule_id_str: String, slots: [String]) -> String

elp/src/lang_profile_ca.el

@@ -0,0 +1,72 @@
+;;; lang_profile_ca.el — Catalan language profile for ELP.
+;;; Mirrors lang_profile_it / _es / _pt; keys the realizer's construction switches.
+;;; Catalan is the CLOSEST Romance sibling to the shared engine (~85% conceptual
+;;; reuse). The deltas: PRONOMS FEBLES with four position allomorphs, l'-elision,
+;;; del/al/pel contractions, the periphrastic preterite (vaig+INF), and NO
+;;; essere/avere split (perfect aux is always HAVER; ser/estar is only the copula).
+
+(lang_profile_ca
+  (language        "Catalan")
+  (iso639          "ca")
+  (family          "Romance")
+
+  ;; ── core typology flags ────────────────────────────────────────────────
+  (pro-drop            yes)    ; null subjects default; overt pronoun = emphatic
+  (obligatory-subject  no)
+  (grammatical-gender  yes)    ; m/f; full NP agreement (art + adj + participle)
+  (do-support          no)
+  (subject-aux-inversion no)   ; yes/no Q = declarative order + '?'; no inversion
+  (article-selection   "el/la/l'/els/les ; un/una/uns/unes")  ; l'-ELISION:
+                               ; el/la -> l' before vowel or (silent) h, glued to
+                               ; the next word (l'home, l'illa); de -> d' before vowel
+  (article-drives-contraction yes)  ; article choice feeds prep+article contraction
+  (adjective-position  "postnominal-default + small prenominal class")  ; bo/bon,
+                               ; mal, gran, nou, vell, primer, molt... prenominal
+  (question-punct      plain)  ; ? and ! only (no inverted ¿ ¡)
+
+  ;; ── MANDATORY prep+article contractions ────────────────────────────────
+  (contractions        ((de el del) (de els dels)
+                        (a el al) (a els als)
+                        (per el pel) (per els pels)))
+  (contraction-mandatory yes)  ; *de el -> del obligatory
+  (contraction-blocked-before-elision yes)  ; de l'home / a l'home (NO *del home)
+
+  ;; ── clitic system: PRONOMS FEBLES (the headline delta) ──────────────────
+  (clitics             yes)
+  (clitic-allomorphy   four-position)  ; per pronoun, form varies by position+onset:
+                       ; reinforced (em, et, el)  proclitic before a consonant
+                       ; elided     (m', t', l', n') proclitic before a vowel/h
+                       ; full       (-me, -lo, -li) enclitic after a consonant/-r
+                       ; reduced    ('m, 't, 'l, 'ns) enclitic after a vowel
+  (clitic-placement    ((finite proclitic)                ; el veig, no m'ho dóna
+                        (imperative-affirmative enclitic)  ; dóna'm, digues-me
+                        (imperative-negative present-subjunctive) ; no parlis (delta)
+                        (infinitive enclitic)              ; ajudar-me, veure'l
+                        (gerund   enclitic)))              ; fent-ho
+  (clitic-combination  ((me el "me'l") (te el "te'l") (se el "se'l")
+                        (me la "me la") (me en "me'n")
+                        (li el "l'hi") (li en "n'hi")))    ; dative+accusative clusters
+  (clitic-particles    (hi en ho))  ; locative hi, partitive/genitive en, neuter ho
+
+  ;; ── verb / aspect system ───────────────────────────────────────────────
+  (finite-agreement    "person+number (6-way)")
+  (tenses              (present imperfet preterit-simple perifrastic-preterit futur
+                        condicional subjuntiu-present subjuntiu-imperfet imperatiu))
+  (periphrastic-preterite "vaig/vas/va/vam/vau/van + INFINITIVE")  ; << hallmark CA
+                               ; (vaig cantar = 'I sang'); coexists w/ synthetic pret.
+  (compound-past       "pretèrit perfet = haver(present) + participle")
+  (perfect-aux         "HAVER only")   ; << NO essere/avere split (simpler than IT)
+  (participle-agreement ((haver preceding-acc-clitic)))  ; les he vistes; else invariable
+  (progressive-aux     "estar + gerundi")
+  (copula              "ser / estar")  ; ser: identity/essential/origin; estar:
+                               ; location + transient state (estic cansat, és a casa)
+  (passive-aux         "ser (+ per-agent)")
+  (future              inflectional)   ; cantaré, serà
+  (comparative         "més/menys ADJ que")
+
+  ;; ── SACRED safety bar (shared with es/pt/it/en) ────────────────────────
+  (negation-faithful   yes)    ; polarity never dropped/inverted; unplaceable -> FLAG
+  (negation            "no (preverbal) + optional 'pas' + concord")  ; no...res/
+                               ; ningú/mai/cap/gens/enlloc
+  (negative-concord    yes)    ; preverbal negative subject (ningú) keeps 'no'
+  (neg-reinforcer      pas))   ; optional (no ho faré pas)

elp/src/lang_profile_de.el

@@ -0,0 +1,41 @@
+;;; lang_profile_de.el — German language profile for ELP.
+;;; Mirrors lang_profile_en / lang_profile_es. Keys the realizer's construction
+;;; switches. German is the largest Germanic delta from the EN engine: V2 word
+;;; order, four morphological cases, and separable-prefix verbs.
+
+(lang_profile_de
+  (language        "German")
+  (iso639          "de")
+  (family          "Germanic")
+  (neighbor-base   "en")     ; realized by extending the English (Germanic) engine
+
+  ;; ── core typology flags ────────────────────────────────────────────────
+  (pro-drop            no)          ; obligatory subject in finite clauses
+  (obligatory-subject  yes)
+  (grammatical-gender  (m f n))     ; three genders; drives article + adj declension
+  (case-system         (nom acc dat gen))   ; four cases on articles/adjs/nouns
+  (word-order          V2)          ; finite verb 2nd in main clause
+  (subordinate-order   verb-final)  ; "..., dass er den Hund SIEHT."
+  (separable-verbs     yes)         ; aufstehen -> "steht ... auf"; ppart "aufgestanden"
+  (do-support          no)          ; German negates/questions the finite verb directly
+  (subject-verb-inversion yes)      ; yes/no Q fronts finite verb; wh-Q fills Vorfeld
+  (article-selection   "der/die/das + ein/kein")   ; declined by case x gender x number
+  (adjective-position  prenominal)
+  (adjective-declension (strong weak mixed))  ; chosen by the determiner type
+  (noun-capitalization yes)
+
+  ;; ── verb / aspect system ───────────────────────────────────────────────
+  (finite-agreement    "person-and-number")   ; full present/past paradigm
+  (auxiliary-order      (modal tense-aux perfect passive main))
+  (perfect-aux         (haben sein))   ; sein for intransitive motion/change verbs
+  (passive-aux         "werden")
+  (future              "werden + infinitive")
+  (comparative         "synthetic (-er / -st, with umlaut)")
+
+  ;; ── negation ───────────────────────────────────────────────────────────
+  (negation-markers    (nicht kein))   ; kein- negates an indefinite NP; nicht else
+  (negation-faithful   yes)            ; SACRED: polarity never dropped/inverted -> FLAG
+
+  ;; ── lexicon provenance ─────────────────────────────────────────────────
+  (lexicon-source      "UniMorph deu (primary) + kaikki.org German (gender override)")
+  (lexicon-license     "CC-BY-SA 3.0 / GFDL"))

elp/src/lang_profile_en.el

@@ -0,0 +1,41 @@
+;;; lang_profile_en.el — English language profile for ELP.
+;;; Mirrors lang_profile_es / lang_profile_pt; keys the realizer's construction
+;;; switches. English is typologically distinct from the Romance builds, so the
+;;; flags differ where the grammar differs.
+
+(lang_profile_en
+  (language        "English")
+  (iso639          "en")
+  (family          "Germanic")
+
+  ;; ── core typology flags ────────────────────────────────────────────────
+  (pro-drop            no)     ; OBLIGATORY subjects — missing subject is FLAGGED
+  (obligatory-subject  yes)
+  (grammatical-gender  no)     ; natural gender only (he/she/it), no NP agreement
+  (do-support          yes)    ; negation & questions of lexical verbs insert do/does/did
+  (subject-aux-inversion yes)  ; yes/no + non-subject wh questions invert the operator
+  (article-selection   "a/an/the")  ; a/an resolved PHONOLOGICALLY (an hour, a university)
+  (adjective-position  prenominal)   ; attributive adjectives precede the noun; invariant
+  (has-tag-questions   yes)          ; "...doesn't he?" — operator + reversed polarity
+  (has-there-existential yes)        ; "there is/are/have been ..."
+  (possessive-clitic   "'s")         ; saxon genitive; plural in -s -> bare apostrophe
+  (question-punct      plain)        ; ? and ! only (no inverted marks)
+
+  ;; ── verb / aspect system ───────────────────────────────────────────────
+  (finite-agreement    "3sg-present-only")  ; only 3sg present -s (+ suppletive be)
+  (auxiliary-order      (modal perfect progressive passive main))
+  (perfect-aux         "have")   ; have + past participle
+  (progressive-aux     "be")     ; be + present participle
+  (passive-aux         "be")     ; be + past participle (+ by-agent)
+  (future              "will + base")   ; no inflectional future
+  (comparative         "synthetic-or-periphrastic")  ; -er/-est vs more/most by syllables
+
+  ;; ── SACRED safety bar (shared with es/pt) ──────────────────────────────
+  (negation-faithful   yes)      ; polarity never dropped/inverted; unplaceable -> FLAG
+
+  ;; ── DIALECT overlay (post-realization, one core -> US/UK/AU) ────────────
+  (dialect             US)       ; default; profile field switches the overlay
+  (dialects            (US UK AU))
+  (dialect-canonical   US)       ; core is authored in US orthography
+  (dialect-overlay     "dialect_en.to_dialect")  ; orthography + lexis + grammar prefs
+  (dialect-covers      (spelling lexis collective-agreement gotten/got)))

elp/src/lang_profile_es.el

@@ -0,0 +1,45 @@
+;;; lang_profile_es.el — Spanish language profile for ELP.
+;;; Keys the realizer's construction switches. Mirrors lang_profile_en / _pt.
+
+(lang_profile_es
+  (language        "Spanish")
+  (iso639          "es")
+  (family          "Romance")
+
+  ;; -- core typology flags -------------------------------------------------
+  (pro-drop            yes)    ; subjects routinely dropped; agreement carries person
+  (obligatory-subject  no)
+  (grammatical-gender  yes)    ; m/f on every noun; article+adjective AGREE
+  (gender-source       lexicon); REAL per-noun gender from UniMorph — NOT a heuristic
+  (do-support          no)
+  (subject-aux-inversion no)   ; questions by intonation/punctuation, not inversion
+  (question-strategy   intonation)
+  (article-selection   "el/la/los/las un/una/unos/unas")
+  (stressed-a-rule     yes)    ; fem sg noun in stressed a-/ha- takes el/un (el agua)
+  (adjective-position  postnominal) ; default post; a few prenominal + apocope
+  (adjective-agreement "gender+number")
+  (question-punct      inverted)    ; opening ¿ ¡ required
+
+  ;; -- MANDATORY CONTRACTIONS (coordinator quality bar) --------------------
+  (contractions        ((de el "del") (a el "al")))
+  (contraction-mandatory yes)  ; 'de el'/'a el' MUST surface as del/al
+
+  ;; -- verb / aspect system ------------------------------------------------
+  (verb-classes        (ar er ir))
+  (tenses              (present preterite imperfect future conditional))
+  (moods               (ind sbjv imp))
+  (finite-agreement    "person+number (6 slots)")
+  (perfect-aux         "haber")  ; haber + past participle (invariant -o)
+  (progressive-aux     "estar")  ; estar + gerund
+  (passive-aux         "ser")    ; ser + participle (agrees) + por-agent
+  (copula-split        "ser/estar")  ; permanent vs stage-level
+  (future              "infinitive + é/ás/á/emos/éis/án")
+
+  ;; -- clitics / government ------------------------------------------------
+  (object-clitics      yes)      ; me te lo la le nos os los las; proclisis/enclisis
+  (clitic-order        "se II I III (le+lo -> se lo)")
+  (enclisis            "imperative/infinitive/gerund + accent repair (dá+me+lo->dámelo)")
+  (verb-prep-government yes)     ; verbs select prep (protestar+contra, escapar+de)
+
+  ;; -- SACRED safety bar (shared with en/pt) -------------------------------
+  (negation-faithful   yes))     ; polarity never dropped/inverted; unplaceable -> FLAG

elp/src/lang_profile_fr.el

@@ -0,0 +1,74 @@
+;;; lang_profile_fr.el — French language profile for ELP.
+;;; Mirrors lang_profile_it / lang_profile_es; keys the realizer's construction
+;;; switches. French is a Romance sibling (~54% of the realizer code and the whole
+;;; clause-engine architecture reused), but carries the family's biggest surface
+;;; deltas: NOT pro-drop, DISCONTINUOUS negation, and an orthography/phonology
+;;; mismatch (elision, liaison) that makes exact-match genuinely hard.
+
+(lang_profile_fr
+  (language        "French")
+  (iso639          "fr")
+  (family          "Romance")
+
+  ;; ── core typology flags ────────────────────────────────────────────────
+  (pro-drop            no)     ; << French-specific: subject clitic OBLIGATORY
+  (obligatory-subject  yes)    ; je/tu/il/elle/nous/vous/ils/elles always overt
+  (grammatical-gender  yes)    ; m/f; full NP agreement (art + adj + participle)
+  (do-support          no)
+  (subject-aux-inversion optional)  ; est-ce que (default) OR clitic inversion (vas-tu)
+  (article-selection   "le/la/l'/les ; un/une/des ; PARTITIVE du/de la/de l'/des")
+  (article-drives-contraction yes)  ; à+le=au, de+le=du feed off article choice
+  (adjective-position  "postnominal-default + prenominal-BAGS")  ; beau/bon/grand/
+                               ; petit/jeune/vieux/nouveau + ordinals prenominal
+                               ; (beau->bel, nouveau->nouvel, vieux->vieil / vowel)
+  (question-punct      "space-before")  ; French typography: ' ?' ' !' (no ¿¡)
+
+  ;; ── elision (orthography/phonology mismatch — French-specific) ──────────
+  (elision             ((le l') (la l') (je j') (ne n') (de d') (que qu')
+                        (me m') (te t') (se s') (ce c')))  ; before vowel / h-muet
+  (elision-h-muet      yes)    ; l'homme, l'hôpital (h-aspiré exception list kept)
+  (liaison             noted-not-modeled)  ; phonological, not written in surface
+
+  ;; ── MANDATORY prep+article contractions ────────────────────────────────
+  (contractions        ((à le au) (à les aux) (de le du) (de les des)))
+  (contraction-mandatory yes)  ; *à le -> au obligatory; à la / à l' uncontracted
+  (partitive           ((m-sg du) (f-sg "de la") (vowel "de l'") (pl des)))
+  (partitive-under-neg "de")   ; << gap in current build: 'ne … pas de pain'
+
+  ;; ── clitic system ──────────────────────────────────────────────────────
+  (clitics             yes)
+  (clitic-order        (me te se nous vous | le la les | lui leur | y | en))
+  (clitic-placement    ((finite proclitic)             ; je le lui donne
+                        (imperative-affirmative enclitic-hyphen)  ; donne-le-moi
+                        (imperative-negative "ne+proclitic+verb+pas")  ; ne le donne pas
+                        (infinitive enclitic)))         ; PARTIAL: clitic-climbing
+                                                        ; onto infinitive under modal
+  (clitic-imperative-shift ((me moi) (te toi)))  ; final me/te -> moi/toi (donne-moi)
+  (clitic-particles    (y en))  ; locative y, partitive/genitive en
+
+  ;; ── verb / aspect system ───────────────────────────────────────────────
+  (finite-agreement    "person+number (written; many homophones)")
+  (tenses              (présent imparfait passé-simple futur conditionnel
+                        subjonctif-présent subjonctif-imparfait impératif))
+  (compound-past       "passé-composé = aux(present) + participe passé")
+  (perfect-aux         "être/avoir (LEXICAL selection)")  ; << French-specific
+  (etre-aux-class      "intransitive motion/change (aller venir arriver partir
+                        entrer sortir monter descendre naître mourir rester
+                        tomber retourner passer devenir revenir rentrer) + ALL
+                        pronominal verbs")
+  (participle-agreement ((être subject)               ; elle est allée / elles venues
+                         (avoir preceding-direct-object)))  ; je les ai vus
+  (progressive         "être en train de + infinitif")  ; no dedicated aux
+  (copula              "être (single; no ser/estar, no essere/stare)")
+  (passive-aux         "être (+ par-agent)")
+  (future              inflectional)         ; parlera, sera
+  (comparative         "plus/moins ADJ que")
+  (superlative         "le/la plus ADJ (de …)")   ; PARTIAL word-order in build
+
+  ;; ── SACRED safety bar (shared with es/pt/it/en) ────────────────────────
+  (negation-faithful   yes)    ; polarity never dropped/inverted; unplaceable -> FLAG
+  (negation            "DISCONTINUOUS: ne (preverbal) … pas/jamais/rien/personne/
+                        plus/guère/que (postverbal)")  ; << biggest structural delta
+  (negation-ne-elides  yes)    ; ne -> n' before vowel (n'ai pas vu)
+  (negation-passe-composé "ne + aux + pas + participe")  ; n'ai pas vu
+  (negative-concord    partial))  ; personne/rien as arguments post-participle

elp/src/lang_profile_it.el

@@ -0,0 +1,70 @@
+;;; lang_profile_it.el — Italian language profile for ELP.
+;;; Mirrors lang_profile_es / lang_profile_pt; keys the realizer's construction
+;;; switches. Italian is a Romance sibling, so ~85% of the flags match ES/PT; the
+;;; essere/avere auxiliary split and phonological article selection are the deltas.
+
+(lang_profile_it
+  (language        "Italian")
+  (iso639          "it")
+  (family          "Romance")
+
+  ;; ── core typology flags ────────────────────────────────────────────────
+  (pro-drop            yes)    ; null subjects default; overt pronoun = emphatic
+  (obligatory-subject  no)
+  (grammatical-gender  yes)    ; m/f; full NP agreement (art + adj + participle)
+  (do-support          no)
+  (subject-aux-inversion no)   ; yes/no Q = declarative order + '?'; no inversion
+  (article-selection   "il/lo/l'/i/gli + la/l'/le ; un/uno/un'/una")  ; PHONOLOGICAL:
+                               ; lo/gli/uno before s+cons, z, gn, ps, pn, x, y, i+V;
+                               ; l'/un' before a vowel (elision, glued to next word)
+  (article-drives-contraction yes)  ; article choice feeds the prep+art contraction
+  (adjective-position  "postnominal-default + prenominal-class")  ; bello/buono/grande
+                               ; /nuovo/vecchio/primo... prenominal (with apocope)
+  (question-punct      plain)  ; ? and ! only (no inverted ¿ ¡)
+
+  ;; ── MANDATORY prep+article contractions ────────────────────────────────
+  (contractions        ((di il del) (di lo dello) (di la della) (di i dei)
+                        (di gli degli) (di le delle) (di l' dell')
+                        (a il al) (a lo allo) (a la alla) (a i ai) (a gli agli)
+                        (a le alle) (a l' all')
+                        (da il dal) (da la dalla) (da gli dagli) (da l' dall')
+                        (in il nel) (in la nella) (in gli negli) (in l' nell')
+                        (su il sul) (su la sulla) (su gli sugli) (su l' sull')))
+  (contraction-mandatory yes)  ; *di il -> del is obligatory, never uncontracted
+  (prep-no-contract    (per tra fra))  ; per la strada (NOT *perla)
+
+  ;; ── clitic system ──────────────────────────────────────────────────────
+  (clitics             yes)
+  (clitic-placement    ((finite proclitic)        ; lo vedo, non me lo dà
+                        (imperative-affirmative enclitic)   ; dammelo, guardalo
+                        (imperative-negative-tu  non+infinitive)  ; non parlare / non lo fare
+                        (infinitive enclitic)      ; vederlo, aiutarmi (drop -e)
+                        (gerund   enclitic)))      ; dandolo
+  (clitic-combination  ((mi lo "me lo") (ti lo "te lo") (ci lo "ce lo")
+                        (vi lo "ve lo") (si lo "se lo")
+                        (gli lo "glielo") (le lo "glielo")))  ; glielo = ONE word
+  (clitic-particles    (ci ne))  ; locative ci, partitive ne
+  (raddoppiamento      (da fa di va sta))  ; monosyllabic imper double clitic: dammelo
+
+  ;; ── verb / aspect system ───────────────────────────────────────────────
+  (finite-agreement    "person+number (6-way)")
+  (tenses              (presente imperfetto passato-remoto futuro condizionale
+                        congiuntivo-presente congiuntivo-imperfetto imperativo))
+  (compound-past       "passato-prossimo = aux(present) + participle")
+  (perfect-aux         "essere/avere (LEXICAL selection)")  ; << Italian-specific
+  (essere-aux-class    unaccusative)  ; motion/change-of-state/copular/pronominal
+                                      ; (andare venire nascere morire diventare piacere
+                                      ;  + ALL reflexives) -> essere
+  (participle-agreement ((essere subject)             ; è andata / sono arrivati
+                         (avere preceding-acc-clitic)))  ; li ho visti
+  (progressive-aux     "stare + gerundio")   ; sto parlando
+  (copula              "essere (default) / stare (state: sto bene)")
+  (passive-aux         "essere / venire (+ da-agent)")
+  (future              inflectional)         ; parlerò, sarà
+  (comparative         "più/meno ADJ di")
+
+  ;; ── SACRED safety bar (shared with es/pt/en) ───────────────────────────
+  (negation-faithful   yes)    ; polarity never dropped/inverted; unplaceable -> FLAG
+  (negation            "non (preverbal) + concord")  ; non...niente/nessuno/mai/più
+  (negative-concord    yes)    ; preverbal negative word (nessuno/niente) suppresses non
+  (neg-adverb-position between-aux-and-participle))  ; non ho MAI visto

elp/src/lang_profile_la.el

@@ -0,0 +1,30 @@
+;;; lang_profile_la.el — Latin language profile for ELP.
+;;; Keys the realizer's construction switches. Companion to morphology-la.el.
+
+(lang_profile_la
+  (language        "Latin")
+  (iso639          "la")
+  (family          "Italic")
+
+  ;; -- core typology flags -------------------------------------------------
+  (pro-drop            yes)     ; person carried by verb ending; subjects dropped
+  (obligatory-subject  no)
+  (grammatical-gender  yes)     ; m/f/n; adjective AGREES in case+gender+number
+  (gender-source       lexicon) ; REAL per-noun gender from UniMorph lat
+  (articles            none)    ; Latin has no articles
+  (case-system         yes)     ; NOM GEN DAT ACC ABL VOC (+ rare LOC)
+  (cases               (nom gen dat acc abl voc))
+  (word-order          "SOV (default; free order, case-marked)")
+  (adjective-position  "either (case agreement carries the link)")
+  (adjective-agreement "case+gender+number")
+
+  ;; -- verb / aspect system ------------------------------------------------
+  (verb-classes        (1 2 3 3io 4))  ; four conjugations + i-stem 3rd
+  (tenses              (present imperfect future perfect pluperfect futureperfect))
+  (moods               (indicative subjunctive imperative infinitive))
+  (voices              (active passive))
+  (finite-agreement    "person+number (6 slots)")
+  (citation            "principal parts: pres-1sg / pres-inf / perf-participle")
+
+  ;; -- SACRED safety bar ---------------------------------------------------
+  (negation-faithful   yes))     ; polarity never dropped/inverted

elp/src/lang_profile_pt.el

@@ -0,0 +1,40 @@
+;;; lang_profile_pt.el — Portuguese language profile for ELP.
+;;; Keys the realizer's construction switches. Mirrors lang_profile_es.
+
+(lang_profile_pt
+  (language        "Portuguese")
+  (iso639          "pt")
+  (family          "Romance")
+
+  ;; -- core typology flags -------------------------------------------------
+  (pro-drop            yes)     ; subjects routinely dropped; agreement carries person
+  (obligatory-subject  no)
+  (grammatical-gender  yes)     ; m/f on every noun; article+adjective AGREE
+  (gender-source       lexicon) ; REAL per-noun gender from UniMorph por / kaikki
+  (do-support          no)
+  (subject-aux-inversion no)
+  (question-strategy   intonation)
+  (article-selection   "o/a/os/as um/uma/uns/umas")
+  (adjective-position  postnominal)
+  (adjective-agreement "gender+number")
+
+  ;; -- MANDATORY CONTRACTIONS (prep + article) -----------------------------
+  (contractions        ((de o "do") (de a "da") (em o "no") (em a "na")
+                         (a o "ao") (a a "à") (por o "pelo") (por a "pela")))
+  (contraction-mandatory yes)
+
+  ;; -- verb / aspect system ------------------------------------------------
+  (verb-classes        (ar er ir))
+  (tenses              (present preterite imperfect future conditional))
+  (moods               (ind sbjv imp))
+  (finite-agreement    "person+number (6 slots)")
+  (perfect-aux         "ter")   ; ter + past participle
+  (copula-split        "ser/estar")
+  (personal-infinitive yes)     ; distinctive PT inflected infinitive
+
+  ;; -- clitics / government ------------------------------------------------
+  (object-clitics      yes)     ; mesoclisis/enclisis/proclisis by context
+  (verb-prep-government yes)
+
+  ;; -- SACRED safety bar ---------------------------------------------------
+  (negation-faithful   yes))

elp/src/lang_profile_ro.el

@@ -0,0 +1,71 @@
+;;; lang_profile_ro.el — Romanian language profile for ELP.
+;;; Romanian is the BIG typological delta of the Romance family. The verb/clause
+;;; engine and the SACRED negation contract mirror the ES/PT/IT core, but the
+;;; NOMINAL system is genuinely new: a SUFFIXED definite article, preserved CASE,
+;;; a NEUTER gender, and a VOCATIVE. Those flags mark where the shared engine was
+;;; extended rather than reused.
+
+(lang_profile_ro
+  (language        "Romanian")
+  (iso639          "ro")
+  (family          "Romance (Eastern / Balkan)")
+
+  ;; ── core typology flags ────────────────────────────────────────────────
+  (pro-drop            yes)    ; null subjects default; overt pronoun = emphatic
+  (obligatory-subject  no)
+  (grammatical-gender  yes)    ; m / f / NEUTER (n)
+  (neuter-gender       yes)    ; << ROMANIAN-SPECIFIC: masc-agreeing SG, fem-agreeing PL
+                               ;    (un tren nou / două trenuri noi)
+  (do-support          no)
+  (subject-aux-inversion no)   ; yes/no Q = declarative order + '?'
+  (question-punct      plain)  ; ? and ! only
+
+  ;; ── SUFFIXED DEFINITE ARTICLE (the headline engine extension) ───────────
+  (definite-article    suffixed)     ; << UNIQUE IN ROMANCE: enclitic on the noun
+  (definite-forms      ((m/n sg "-ul / -le / -l : om->omul, câine->câinele, codru->codrul")
+                        (f   sg "-a / -ea / -ua : casă->casa, carte->cartea, stea->steaua")
+                        (m   pl "-i : oameni->oamenii")
+                        (f/n pl "-le : case->casele, trenuri->trenurile")))
+  (article-host        ((no-prenom-adj noun)      ; omul bun
+                        (prenom-adj    adjective)))  ; bunul om (adj carries the article)
+  (indefinite-article  ((m/n "un") (f "o") (pl "niște") (gen/dat-pl "unor")))
+
+  ;; ── CASE (preserved; NOM/ACC vs GEN/DAT) ────────────────────────────────
+  (case                (nom/acc gen/dat vocative))   ; << ROMANIAN-SPECIFIC
+  (case-syncretism     "nom=acc ; gen=dat")
+  (genitive-marking    "gen/dat definite: -lui (m/n), -ei/-i (f), -lor (pl)")
+  (genitival-article   ((m sg "al") (f sg "a") (m pl "ai") (f/n pl "ale")))  ; o carte a lui
+  (possession          "definite-head + gen/dat possessor: casa băiatului")
+  (vocative            ((m sg "-ule/-e : omule, băiete") (f sg "-o : Mario, fato")
+                        (pl "-lor")))
+
+  ;; ── verb / aspect system ────────────────────────────────────────────────
+  (finite-agreement    "person+number (6-way)")
+  (tenses              (prezent imperfect perfect-simplu conjunctiv-prezent
+                        imperativ (periphrastic: perfect-compus viitor conditional)))
+  (compound-past       "perfectul compus = a-avea-clitic + INVARIABLE participle")
+  (perfect-aux         "a avea (am/ai/a/am/ați/au) — ONE auxiliary for ALL verbs")
+  (perfect-aux-split   no)     ; << SIMPLER than Italian: no essere/avere selection
+  (participle-agreement none)  ; invariable in the perfect compus (agrees only as
+                               ;   an adjective / in the passive)
+  (future              "voi/vei/va/vom/veți/vor + infinitive (viitor literar)")
+  (conditional         "aș/ai/ar/am/ați/ar + infinitive")
+  (subjunctive         "conjunctiv: particle 'să' + subjunctive present")
+  (modal-complement    "modal + să + subjunctive (vreau să merg, poți să ajuți)")
+  (copula              "a fi")
+  (passive             "a fi + participle (participle AGREES like an adjective)")
+  (comparative         "mai / mai puțin ADJ decât")
+
+  ;; ── clitic system (partial — see honest gaps) ───────────────────────────
+  (clitics             yes)
+  (clitic-set          ((acc mă te îl o ne vă îi le) (dat îmi îți îi ne vă le)
+                        (refl mă te se ne vă se)))
+  (clitic-placement    ((finite proclitic)          ; îmi place, o văd
+                        (perfect-compus elision)     ; << m-am, l-am, i-am (PARTIAL)
+                        (imperative-affirmative enclitic)))  ; dă-mi (PARTIAL)
+
+  ;; ── SACRED safety bar (shared with es/pt/it/en) ─────────────────────────
+  (negation-faithful   yes)    ; polarity never dropped/inverted; unplaceable -> FLAG
+  (negation            "nu (single preverbal marker) + concord")
+  (negative-concord    yes)    ; nu … nimic / nimeni / niciodată / niciun
+  (negative-imperative "nu + INFINITIVE : nu pleca! (KNOWN GAP: uses imperative stem)"))

elp/src/language-profile.elh

@@ -1,46 +1,46 @@
-// auto-generated by elc --emit-header - do not edit
-extern fn lang_profile(code: String, word_order: String, morph_type: String, has_case: String, has_gender: String, script_dir: String, agreement: String, null_subject: String) -> Any
-extern fn lang_get(profile: Any, key: String) -> String
-extern fn lang_profile_en() -> Any
-extern fn lang_profile_ja() -> Any
-extern fn lang_profile_ar() -> Any
-extern fn lang_profile_zh() -> Any
-extern fn lang_profile_de() -> Any
-extern fn lang_profile_es() -> Any
-extern fn lang_profile_fi() -> Any
-extern fn lang_profile_sw() -> Any
-extern fn lang_profile_hi() -> Any
-extern fn lang_profile_ru() -> Any
-extern fn lang_profile_fr() -> Any
-extern fn lang_profile_la() -> Any
-extern fn lang_profile_he() -> Any
-extern fn lang_profile_sa() -> Any
-extern fn lang_profile_got() -> Any
-extern fn lang_profile_non() -> Any
-extern fn lang_profile_enm() -> Any
-extern fn lang_profile_pi() -> Any
-extern fn lang_profile_grc() -> Any
-extern fn lang_profile_ang() -> Any
-extern fn lang_profile_fro() -> Any
-extern fn lang_profile_goh() -> Any
-extern fn lang_profile_sga() -> Any
-extern fn lang_profile_txb() -> Any
-extern fn lang_profile_peo() -> Any
-extern fn lang_profile_akk() -> Any
-extern fn lang_profile_uga() -> Any
-extern fn lang_profile_egy() -> Any
-extern fn lang_profile_sux() -> Any
-extern fn lang_profile_gez() -> Any
-extern fn lang_profile_cop() -> Any
-extern fn lang_from_code(code: String) -> Any
-extern fn lang_default() -> Any
-extern fn lang_is_isolating(profile: Any) -> Bool
-extern fn lang_is_agglutinative(profile: Any) -> Bool
-extern fn lang_is_fusional(profile: Any) -> Bool
-extern fn lang_is_polysynthetic(profile: Any) -> Bool
-extern fn lang_is_rtl(profile: Any) -> Bool
-extern fn lang_has_null_subject(profile: Any) -> Bool
-extern fn lang_has_case(profile: Any) -> Bool
-extern fn lang_has_gender(profile: Any) -> Bool
-extern fn lang_word_order(profile: Any) -> String
-extern fn lang_code(profile: Any) -> String
+// auto-generated by elc --emit-header — do not edit
+extern fn lang_profile(code: String, word_order: String, morph_type: String, has_case: String, has_gender: String, script_dir: String, agreement: String, null_subject: String) -> [String]
+extern fn lang_get(profile: [String], key: String) -> String
+extern fn lang_profile_en() -> [String]
+extern fn lang_profile_ja() -> [String]
+extern fn lang_profile_ar() -> [String]
+extern fn lang_profile_zh() -> [String]
+extern fn lang_profile_de() -> [String]
+extern fn lang_profile_es() -> [String]
+extern fn lang_profile_fi() -> [String]
+extern fn lang_profile_sw() -> [String]
+extern fn lang_profile_hi() -> [String]
+extern fn lang_profile_ru() -> [String]
+extern fn lang_profile_fr() -> [String]
+extern fn lang_profile_la() -> [String]
+extern fn lang_profile_he() -> [String]
+extern fn lang_profile_sa() -> [String]
+extern fn lang_profile_got() -> [String]
+extern fn lang_profile_non() -> [String]
+extern fn lang_profile_enm() -> [String]
+extern fn lang_profile_pi() -> [String]
+extern fn lang_profile_grc() -> [String]
+extern fn lang_profile_ang() -> [String]
+extern fn lang_profile_fro() -> [String]
+extern fn lang_profile_goh() -> [String]
+extern fn lang_profile_sga() -> [String]
+extern fn lang_profile_txb() -> [String]
+extern fn lang_profile_peo() -> [String]
+extern fn lang_profile_akk() -> [String]
+extern fn lang_profile_uga() -> [String]
+extern fn lang_profile_egy() -> [String]
+extern fn lang_profile_sux() -> [String]
+extern fn lang_profile_gez() -> [String]
+extern fn lang_profile_cop() -> [String]
+extern fn lang_from_code(code: String) -> [String]
+extern fn lang_default() -> [String]
+extern fn lang_is_isolating(profile: [String]) -> Bool
+extern fn lang_is_agglutinative(profile: [String]) -> Bool
+extern fn lang_is_fusional(profile: [String]) -> Bool
+extern fn lang_is_polysynthetic(profile: [String]) -> Bool
+extern fn lang_is_rtl(profile: [String]) -> Bool
+extern fn lang_has_null_subject(profile: [String]) -> Bool
+extern fn lang_has_case(profile: [String]) -> Bool
+extern fn lang_has_gender(profile: [String]) -> Bool
+extern fn lang_word_order(profile: [String]) -> String
+extern fn lang_code(profile: [String]) -> String

elp/src/morphology-akk.el

@@ -56,6 +56,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn akk_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-akk.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn akk_str_ends(s: String, suf: String) -> Bool
 extern fn akk_str_len(s: String) -> Int
 extern fn akk_str_drop_last(s: String, n: Int) -> String

elp/src/morphology-ang.el

@@ -36,6 +36,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn ang_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-ang.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn ang_str_ends(s: String, suf: String) -> Bool
 extern fn ang_str_drop_last(s: String, n: Int) -> String
 extern fn ang_str_last_char(s: String) -> String

elp/src/morphology-ar.el

@@ -21,6 +21,7 @@
 
 // ── String helpers ────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn ar_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-ar.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn ar_str_ends(s: String, suf: String) -> Bool
 extern fn ar_str_len(s: String) -> Int
 extern fn ar_str_drop_last(s: String, n: Int) -> String

elp/src/morphology-cop.el

@@ -54,6 +54,7 @@
 
 // ── String helpers ──────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn cop_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-cop.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn cop_str_ends(s: String, suf: String) -> Bool
 extern fn cop_str_len(s: String) -> Int
 extern fn cop_drop(s: String, n: Int) -> String

elp/src/morphology-de.el

@@ -26,6 +26,7 @@
 //  Dat:    dem     der     dem     den
 //  Gen:    des     der     des     der
 
+import "morphology.el"
 fn de_article_def(gender: String, gram_case: String, number: String) -> String {
     if str_eq(number, "pl") {
         if str_eq(gram_case, "nom") { return "die" }

elp/src/morphology-de.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn de_article_def(gender: String, gram_case: String, number: String) -> String
 extern fn de_article_indef(gender: String, gram_case: String, number: String) -> String
 extern fn de_article(gender: String, gram_case: String, number: String, definite: String) -> String

elp/src/morphology-egy.el

@@ -52,6 +52,7 @@
 
 // ── String helpers ──────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn egy_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-egy.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn egy_str_ends(s: String, suf: String) -> Bool
 extern fn egy_str_len(s: String) -> Int
 extern fn egy_drop(s: String, n: Int) -> String

elp/src/morphology-enm.el

@@ -31,6 +31,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn enm_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-enm.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn enm_str_ends(s: String, suf: String) -> Bool
 extern fn enm_drop(s: String, n: Int) -> String
 extern fn enm_first_char(s: String) -> String

elp/src/morphology-es.el

@@ -12,6 +12,7 @@
 
 // ── String helpers (local, matching morphology.el conventions) ────────────────
 
+import "morphology.el"
 fn es_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-es.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn es_str_ends(s: String, suf: String) -> Bool
 extern fn es_str_drop_last(s: String, n: Int) -> String
 extern fn es_str_last_char(s: String) -> String

elp/src/morphology-fi.el

@@ -25,6 +25,7 @@
 // If only neutral vowels are found, default to "front" (the conservative choice
 // for borrowed words and those without clear back vowels).
 
+import "morphology.el"
 fn fi_harmony(word: String) -> String {
     let n: Int = str_len(word)
     let i: Int = n - 1

elp/src/morphology-fi.elh

@@ -1,11 +1,11 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn fi_harmony(word: String) -> String
 extern fn fi_suffix(base: String, harmony: String) -> String
 extern fn fi_noun_case(stem: String, gram_case: String, number: String, harmony: String) -> String
 extern fn fi_str_last_char(s: String) -> String
 extern fn fi_apply_case(noun: String, gram_case: String, number: String) -> String
 extern fn fi_verb_stem(dict_form: String) -> String
-extern fn fi_irregular_verb(dict_form: String) -> Any
+extern fn fi_irregular_verb(dict_form: String) -> [String]
 extern fn fi_present_ending(stem: String, person: String, number: String, harmony: String) -> String
 extern fn fi_past_stem(stem: String) -> String
 extern fn fi_past_ending(stem: String, person: String, number: String, harmony: String) -> String
@@ -14,4 +14,4 @@ extern fn fi_negative(verb: String, person: String, number: String) -> String
 extern fn fi_conjugate(verb: String, tense: String, person: String, number: String) -> String
 extern fn fi_question_suffix(harmony: String) -> String
 extern fn fi_make_question(verb_form: String, harmony: String) -> String
-extern fn fi_full_paradigm(noun: String) -> Any
+extern fn fi_full_paradigm(noun: String) -> [String]

elp/src/morphology-fr.el

@@ -19,6 +19,7 @@
 
 // ── String helpers (local, matching morphology.el conventions) ────────────────
 
+import "morphology.el"
 fn fr_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-fr.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn fr_str_ends(s: String, suf: String) -> Bool
 extern fn fr_str_drop_last(s: String, n: Int) -> String
 extern fn fr_str_last_char(s: String) -> String

elp/src/morphology-fro.el

@@ -53,6 +53,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn fro_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-fro.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn fro_str_ends(s: String, suf: String) -> Bool
 extern fn fro_drop(s: String, n: Int) -> String
 extern fn fro_slot(person: String, number: String) -> Int

elp/src/morphology-gez.el

@@ -64,6 +64,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn gez_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-gez.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn gez_str_ends(s: String, suf: String) -> Bool
 extern fn gez_str_len(s: String) -> Int
 extern fn gez_str_drop_last(s: String, n: Int) -> String

elp/src/morphology-goh.el

@@ -48,6 +48,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn goh_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-goh.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn goh_str_ends(s: String, suf: String) -> Bool
 extern fn goh_drop(s: String, n: Int) -> String
 extern fn goh_slot(person: String, number: String) -> Int

elp/src/morphology-got.el

@@ -49,6 +49,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn got_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-got.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn got_str_ends(s: String, suf: String) -> Bool
 extern fn got_str_drop_last(s: String, n: Int) -> String
 extern fn got_slot(person: String, number: String) -> Int

elp/src/morphology-grc.el

@@ -31,6 +31,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn grc_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-grc.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn grc_str_ends(s: String, suf: String) -> Bool
 extern fn grc_str_drop_last(s: String, n: Int) -> String
 extern fn grc_str_last_char(s: String) -> String

elp/src/morphology-he.el

@@ -51,6 +51,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn he_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-he.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn he_str_ends(s: String, suf: String) -> Bool
 extern fn he_str_len(s: String) -> Int
 extern fn he_str_drop_last(s: String, n: Int) -> String

elp/src/morphology-hi.el

@@ -24,6 +24,7 @@
 
 // ── String helpers ────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn hi_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-hi.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn hi_str_ends(s: String, suf: String) -> Bool
 extern fn hi_str_drop_last(s: String, n: Int) -> String
 extern fn hi_str_last_char(s: String) -> String

elp/src/morphology-ja.el

@@ -23,6 +23,7 @@
 // Note: this is a heuristic classifier for romanized input.  For production use
 // with native kana/kanji forms, the dictionary form (辞書形) must be consulted.
 
+import "morphology.el"
 fn ja_verb_group(dict_form: String) -> String {
     // Irregular verbs (exact match on dictionary form)
     if str_eq(dict_form, "する")  { return "irregular" }

elp/src/morphology-ja.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn ja_verb_group(dict_form: String) -> String
 extern fn ja_ichidan_stem(dict_form: String) -> String
 extern fn ja_godan_stem_change(dict_form: String, row: String) -> String

elp/src/morphology-la.el

@@ -25,6 +25,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn la_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-la.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn la_str_ends(s: String, suf: String) -> Bool
 extern fn la_str_drop_last(s: String, n: Int) -> String
 extern fn la_str_last_char(s: String) -> String

elp/src/morphology-non.el

@@ -27,6 +27,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn non_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-non.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn non_str_ends(s: String, suf: String) -> Bool
 extern fn non_drop(s: String, n: Int) -> String
 extern fn non_last(s: String) -> String

elp/src/morphology-peo.el

@@ -31,6 +31,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn peo_drop(s: String, n: Int) -> String {
     let len: Int = str_len(s)
     if n >= len { return "" }

elp/src/morphology-peo.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn peo_drop(s: String, n: Int) -> String
 extern fn peo_ends(s: String, suf: String) -> Bool
 extern fn peo_slot(person: String, number: String) -> Int

elp/src/morphology-pi.el

@@ -30,6 +30,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn pi_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-pi.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn pi_str_ends(s: String, suf: String) -> Bool
 extern fn pi_drop(s: String, n: Int) -> String
 extern fn pi_last_char(s: String) -> String

elp/src/morphology-ru.el

@@ -35,6 +35,7 @@
 // The heuristic returns the most probable gender.  Caller should override
 // for known exceptions (путь, рубль are masc despite -ь).
 
+import "morphology.el"
 fn ru_gender(noun: String) -> String {
     let n: Int = str_len(noun)
     if n == 0 { return "m" }

elp/src/morphology-ru.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn ru_gender(noun: String) -> String
 extern fn ru_stem_type(noun: String, gender: String) -> String
 extern fn ru_noun_case(noun: String, gender: String, gram_case: String, number: String) -> String

elp/src/morphology-sa.el

@@ -42,6 +42,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn sa_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-sa.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn sa_str_ends(s: String, suf: String) -> Bool
 extern fn sa_str_drop_last(s: String, n: Int) -> String
 extern fn sa_slot(person: String, number: String) -> Int

elp/src/morphology-sga.el

@@ -31,6 +31,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn sga_drop(s: String, n: Int) -> String {
     let len: Int = str_len(s)
     if n >= len { return "" }

elp/src/morphology-sga.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn sga_drop(s: String, n: Int) -> String
 extern fn sga_first(s: String) -> String
 extern fn sga_rest(s: String) -> String

elp/src/morphology-sux.el

@@ -53,6 +53,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn sux_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-sux.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn sux_str_ends(s: String, suf: String) -> Bool
 extern fn sux_str_drop_last(s: String, n: Int) -> String
 extern fn sux_str_last_char(s: String) -> String

elp/src/morphology-sw.el

@@ -24,6 +24,7 @@
 
 // ── String helpers ────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn sw_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-sw.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn sw_str_ends(s: String, suf: String) -> Bool
 extern fn sw_str_drop_last(s: String, n: Int) -> String
 extern fn sw_str_first_char(s: String) -> String

elp/src/morphology-txb.el

@@ -30,6 +30,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn txb_drop(s: String, n: Int) -> String {
     let len: Int = str_len(s)
     if n >= len { return "" }

elp/src/morphology-txb.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn txb_drop(s: String, n: Int) -> String
 extern fn txb_ends(s: String, suf: String) -> Bool
 extern fn txb_slot(person: String, number: String) -> Int

elp/src/morphology-uga.el

@@ -48,6 +48,7 @@
 
 // ── String helpers ─────────────────────────────────────────────────────────────
 
+import "morphology.el"
 fn uga_str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }

elp/src/morphology-uga.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn uga_str_ends(s: String, suf: String) -> Bool
 extern fn uga_str_len(s: String) -> Int
 extern fn uga_str_drop_last(s: String, n: Int) -> String

elp/src/morphology.el

@@ -33,6 +33,17 @@
 
 // ── String helpers ────────────────────────────────────────────────────────────
 
+import "language-profile.el"
+import "morphology-es.el"
+import "morphology-fr.el"
+import "morphology-de.el"
+import "morphology-ru.el"
+import "morphology-fi.el"
+import "morphology-ar.el"
+import "morphology-hi.el"
+import "morphology-sw.el"
+import "morphology-la.el"
+import "morphology-ja.el"
 fn str_ends(s: String, suf: String) -> Bool {
     return str_ends_with(s, suf)
 }
@@ -239,6 +250,7 @@ fn en_irregular_verb(base: String) -> [String] {
     if str_eq(base, "cut")     { let r: [String] = ["cut",    "cuts",  "cut",    "cut",     "cutting"];  return r }
     if str_eq(base, "set")     { let r: [String] = ["set",    "sets",  "set",    "set",     "setting"];  return r }
     if str_eq(base, "hit")     { let r: [String] = ["hit",    "hits",  "hit",    "hit",     "hitting"];  return r }
+    if str_eq(base, "fight")   { let r: [String] = ["fight",  "fights","fought", "fought",  "fighting"]; return r }
     return empty
 }
 

elp/src/morphology.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn str_ends(s: String, suf: String) -> Bool
 extern fn str_last_char(s: String) -> String
 extern fn str_last2(s: String) -> String
@@ -8,7 +8,7 @@ extern fn is_vowel(c: String) -> Bool
 extern fn morph_apply_suffix(base: String, suffix: String) -> String
 extern fn en_irregular_plural(word: String) -> String
 extern fn en_irregular_singular(word: String) -> String
-extern fn en_irregular_verb(base: String) -> Any
+extern fn en_irregular_verb(base: String) -> [String]
 extern fn en_verb_3sg(base: String) -> String
 extern fn en_should_double_final(base: String) -> Bool
 extern fn en_verb_past(base: String) -> String
@@ -16,10 +16,10 @@ extern fn en_verb_gerund(base: String) -> String
 extern fn en_pluralize_regular(singular: String) -> String
 extern fn en_verb_form(base: String, tense: String, person: String, number: String) -> String
 extern fn agree_determiner(det: String, noun: String) -> String
-extern fn morph_pluralize(noun: String, profile: Any) -> String
+extern fn morph_pluralize(noun: String, profile: [String]) -> String
 extern fn morph_map_canonical(verb: String, code: String) -> String
-extern fn morph_conjugate(verb: String, tense: String, person: String, number: String, profile: Any) -> String
-extern fn morph_inflect(word: String, features: String, profile: Any) -> String
+extern fn morph_conjugate(verb: String, tense: String, person: String, number: String, profile: [String]) -> String
+extern fn morph_inflect(word: String, features: String, profile: [String]) -> String
 extern fn pluralize(singular: String) -> String
 extern fn singularize(plural: String) -> String
 extern fn verb_form(base: String, tense: String, person: String, number: String) -> String

elp/src/multilingual.el

@@ -0,0 +1,280 @@
+// multilingual.el - the language layer for the native-el interlocutor.
+//
+// Deterministic, NO generative model (ports multilingual.py):
+//   1. ml_detect(text)          -> ISO code  (en/es/pt/it) via stopword + diacritic score
+//   2. ml_tr(key, lang)         -> localized fixed phrase (SACRED per-language yes/no/decline)
+//   3. ml_term(w, lang)         -> PT/ES content term -> EN engram equivalent
+//   4. ml_translate_pred(lemma, lang) -> EN predicate lemma -> target infinitive
+//
+// The Python detector count-weights stopwords and diacritics; here diacritics are
+// scored by PRESENCE (str_contains) rather than codepoint counting, to stay clear
+// of UTF-8 index hazards in the runtime. Faithful enough to classify typical
+// queries; documented simplification.  Depends on: comprehend (cp_tokenize).
+
+// ── 1. language detection ─────────────────────────────────────────────────────
+
+fn ml_stop_en(w: String) -> Bool {
+    if str_eq(w, "the") { return true }
+    if str_eq(w, "does") { return true }
+    if str_eq(w, "do") { return true }
+    if str_eq(w, "did") { return true }
+    if str_eq(w, "what") { return true }
+    if str_eq(w, "who") { return true }
+    if str_eq(w, "is") { return true }
+    if str_eq(w, "are") { return true }
+    if str_eq(w, "how") { return true }
+    if str_eq(w, "you") { return true }
+    if str_eq(w, "your") { return true }
+    if str_eq(w, "of") { return true }
+    if str_eq(w, "to") { return true }
+    if str_eq(w, "and") { return true }
+    if str_eq(w, "for") { return true }
+    if str_eq(w, "explain") { return true }
+    if str_eq(w, "answer") { return true }
+    if str_eq(w, "memory") { return true }
+    if str_eq(w, "with") { return true }
+    if str_eq(w, "not") { return true }
+    if str_eq(w, "store") { return true }
+    return false
+}
+
+fn ml_stop_es(w: String) -> Bool {
+    if str_eq(w, "que") { return true }
+    if str_eq(w, "qué") { return true }
+    if str_eq(w, "una") { return true }
+    if str_eq(w, "usted") { return true }
+    if str_eq(w, "su") { return true }
+    if str_eq(w, "cómo") { return true }
+    if str_eq(w, "como") { return true }
+    if str_eq(w, "cuál") { return true }
+    if str_eq(w, "quién") { return true }
+    if str_eq(w, "está") { return true }
+    if str_eq(w, "es") { return true }
+    if str_eq(w, "los") { return true }
+    if str_eq(w, "las") { return true }
+    if str_eq(w, "del") { return true }
+    if str_eq(w, "al") { return true }
+    if str_eq(w, "explica") { return true }
+    if str_eq(w, "explique") { return true }
+    if str_eq(w, "forma") { return true }
+    if str_eq(w, "con") { return true }
+    if str_eq(w, "memoria") { return true }
+    if str_eq(w, "responde") { return true }
+    return false
+}
+
+fn ml_stop_pt(w: String) -> Bool {
+    if str_eq(w, "que") { return true }
+    if str_eq(w, "uma") { return true }
+    if str_eq(w, "você") { return true }
+    if str_eq(w, "sua") { return true }
+    if str_eq(w, "seu") { return true }
+    if str_eq(w, "como") { return true }
+    if str_eq(w, "memória") { return true }
+    if str_eq(w, "isso") { return true }
+    if str_eq(w, "os") { return true }
+    if str_eq(w, "as") { return true }
+    if str_eq(w, "da") { return true }
+    if str_eq(w, "do") { return true }
+    if str_eq(w, "na") { return true }
+    if str_eq(w, "no") { return true }
+    if str_eq(w, "explica") { return true }
+    if str_eq(w, "forma") { return true }
+    if str_eq(w, "é") { return true }
+    if str_eq(w, "está") { return true }
+    if str_eq(w, "com") { return true }
+    if str_eq(w, "responda") { return true }
+    return false
+}
+
+fn ml_stop_it(w: String) -> Bool {
+    if str_eq(w, "che") { return true }
+    if str_eq(w, "una") { return true }
+    if str_eq(w, "come") { return true }
+    if str_eq(w, "della") { return true }
+    if str_eq(w, "gli") { return true }
+    if str_eq(w, "è") { return true }
+    if str_eq(w, "sono") { return true }
+    if str_eq(w, "questo") { return true }
+    if str_eq(w, "nel") { return true }
+    if str_eq(w, "di") { return true }
+    if str_eq(w, "il") { return true }
+    if str_eq(w, "cosa") { return true }
+    if str_eq(w, "per") { return true }
+    if str_eq(w, "memoria") { return true }
+    if str_eq(w, "spiega") { return true }
+    if str_eq(w, "rispondi") { return true }
+    return false
+}
+
+// diacritic PRESENCE score (weight 3 each; hard overrides weight 8).
+fn ml_dia_score(low: String, lang: String) -> Int {
+    let s: Int = 0
+    if str_eq(lang, "pt") {
+        if str_contains(low, "ã") { let s = s + 3 }
+        if str_contains(low, "õ") { let s = s + 3 }
+        if str_contains(low, "ç") { let s = s + 3 }
+        if str_contains(low, "ê") { let s = s + 3 }
+        if str_contains(low, "á") { let s = s + 3 }
+        // hard PT markers (ã/õ almost never appear outside PT)
+        if str_contains(low, "ã") { let s = s + 8 }
+        if str_contains(low, "õ") { let s = s + 8 }
+    }
+    if str_eq(lang, "es") {
+        if str_contains(low, "ñ") { let s = s + 3 }
+        if str_contains(low, "¿") { let s = s + 3 }
+        if str_contains(low, "¡") { let s = s + 3 }
+        if str_contains(low, "á") { let s = s + 3 }
+        if str_contains(low, "é") { let s = s + 3 }
+        // hard ES markers
+        if str_contains(low, "ñ") { let s = s + 8 }
+        if str_contains(low, "¿") { let s = s + 8 }
+        if str_contains(low, "¡") { let s = s + 8 }
+    }
+    if str_eq(lang, "it") {
+        if str_contains(low, "è") { let s = s + 3 }
+        if str_contains(low, "ì") { let s = s + 3 }
+        if str_contains(low, "ò") { let s = s + 3 }
+    }
+    return s
+}
+
+fn ml_stop_score(toks: [String], lang: String) -> Int {
+    let n: Int = native_list_len(toks)
+    let s: Int = 0
+    let i: Int = 0
+    while i < n {
+        let w: String = native_list_get(toks, i)
+        if str_eq(lang, "en") { if ml_stop_en(w) { let s = s + 2 } }
+        if str_eq(lang, "es") { if ml_stop_es(w) { let s = s + 2 } }
+        if str_eq(lang, "pt") { if ml_stop_pt(w) { let s = s + 2 } }
+        if str_eq(lang, "it") { if ml_stop_it(w) { let s = s + 2 } }
+        let i = i + 1
+    }
+    return s
+}
+
+fn ml_detect(text: String) -> String {
+    if str_eq(text, "") { return "en" }
+    let low: String = str_to_lower(text)
+    let toks: [String] = cp_tokenize(text)
+    // NOTE: el's overloaded `+` mis-compiles two chained function-call Int operands
+    // as string concat (documented in comprehend_gate.el). Bind each call to an Int
+    // var and add vars one at a time so the addition stays integer.
+    let en: Int = ml_stop_score(toks, "en")
+    let es_s: Int = ml_stop_score(toks, "es")
+    let es_d: Int = ml_dia_score(low, "es")
+    let es: Int = es_s + es_d
+    let pt_s: Int = ml_stop_score(toks, "pt")
+    let pt_d: Int = ml_dia_score(low, "pt")
+    let pt: Int = pt_s + pt_d
+    let it_s: Int = ml_stop_score(toks, "it")
+    let it_d: Int = ml_dia_score(low, "it")
+    let it: Int = it_s + it_d
+
+    let best: String = "en"
+    let bs: Int = en
+    if es > bs { let best = "es"; let bs = es }
+    if pt > bs { let best = "pt"; let bs = pt }
+    if it > bs { let best = "it"; let bs = it }
+    // weak signal -> honest fallback to English
+    if bs < 3 { return "en" }
+    return best
+}
+
+// ── 2. localized fixed phrases (SACRED per-language decline/yes/no) ────────────
+
+fn ml_tr(key: String, lang: String) -> String {
+    if str_eq(key, "no_memory") {
+        if str_eq(lang, "pt") { return "Não tenho isso na minha memória." }
+        if str_eq(lang, "es") { return "No tengo eso en mi memoria." }
+        if str_eq(lang, "it") { return "Non ho quello nella mia memoria." }
+        return "I don't have that in my memory."
+    }
+    if str_eq(key, "parse_fail") {
+        if str_eq(lang, "pt") { return "Não consegui interpretar isso." }
+        if str_eq(lang, "es") { return "No pude interpretar eso." }
+        if str_eq(lang, "it") { return "Non sono riuscito a interpretarlo." }
+        return "I didn't parse that."
+    }
+    if str_eq(key, "yes") {
+        if str_eq(lang, "pt") { return "Sim" }
+        if str_eq(lang, "es") { return "Sí" }
+        if str_eq(lang, "it") { return "Sì" }
+        return "Yes"
+    }
+    if str_eq(key, "no") {
+        if str_eq(lang, "pt") { return "Não" }
+        if str_eq(lang, "es") { return "No" }
+        if str_eq(lang, "it") { return "No" }
+        return "No"
+    }
+    if str_eq(key, "identity") {
+        if str_eq(lang, "pt") { return "Sou o Neuron, o engrama com quem você está falando." }
+        if str_eq(lang, "es") { return "Soy Neuron, el engrama con el que estás hablando." }
+        if str_eq(lang, "it") { return "Sono Neuron, l'engramma con cui stai parlando." }
+        return "I'm Neuron, the engram you're speaking with."
+    }
+    return ""
+}
+
+// ── 3. retrieval term lexicon (PT/ES content term -> EN engram equivalent) ─────
+
+fn ml_term(w: String, lang: String) -> String {
+    if str_eq(lang, "en") { return w }
+    if str_eq(w, "saliência") { return "salience" }
+    if str_eq(w, "saliencia") { return "salience" }
+    if str_eq(w, "memória") { return "memory" }
+    if str_eq(w, "memoria") { return "memory" }
+    if str_eq(w, "geometria") { return "geometry" }
+    if str_eq(w, "geometrias") { return "geometry" }
+    if str_eq(w, "geometrías") { return "geometry" }
+    if str_eq(w, "forma") { return "form" }
+    if str_eq(w, "consolidação") { return "consolidation" }
+    if str_eq(w, "consolidación") { return "consolidation" }
+    if str_eq(w, "aprendizagem") { return "learning" }
+    if str_eq(w, "aprendizaje") { return "learning" }
+    if str_eq(w, "nó") { return "node" }
+    if str_eq(w, "nodo") { return "node" }
+    if str_eq(w, "armazenamento") { return "storage" }
+    if str_eq(w, "almacenamiento") { return "storage" }
+    if str_eq(w, "estrutura") { return "structure" }
+    if str_eq(w, "estructura") { return "structure" }
+    return w
+}
+
+// ── 4. predicate translation (EN lemma -> target infinitive; pass-through) ─────
+
+fn ml_translate_pred(lemma: String, lang: String) -> String {
+    if str_eq(lang, "en") { return lemma }
+    if str_eq(lang, "es") {
+        if str_eq(lemma, "store") { return "almacenar" }
+        if str_eq(lemma, "use") { return "usar" }
+        if str_eq(lemma, "have") { return "tener" }
+        if str_eq(lemma, "be") { return "ser" }
+        if str_eq(lemma, "give") { return "dar" }
+        if str_eq(lemma, "make") { return "hacer" }
+        if str_eq(lemma, "learn") { return "aprender" }
+        if str_eq(lemma, "form") { return "formar" }
+        return lemma
+    }
+    if str_eq(lang, "pt") {
+        if str_eq(lemma, "store") { return "armazenar" }
+        if str_eq(lemma, "use") { return "usar" }
+        if str_eq(lemma, "have") { return "ter" }
+        if str_eq(lemma, "be") { return "ser" }
+        if str_eq(lemma, "give") { return "dar" }
+        if str_eq(lemma, "make") { return "fazer" }
+        if str_eq(lemma, "learn") { return "aprender" }
+        if str_eq(lemma, "form") { return "formar" }
+        return lemma
+    }
+    if str_eq(lang, "it") {
+        if str_eq(lemma, "store") { return "memorizzare" }
+        if str_eq(lemma, "use") { return "usare" }
+        if str_eq(lemma, "have") { return "avere" }
+        if str_eq(lemma, "be") { return "essere" }
+        return lemma
+    }
+    return lemma
+}

elp/src/propositions.el

@@ -0,0 +1,140 @@
+// propositions.el - the READ primitive over the engram's OWN memories, native el.
+//
+// Free memory text -> structured PROPOSITIONS (triples):
+//     (subject, predicate, object, modifiers, polarity, tense, source, confidence)
+//
+// This is comprehension turned inward: the Python reference (propositions.py) ran
+// spaCy's dependency parser over each memory sentence and walked the arcs. Here
+// the spaCy role is filled by the el-native parser (comprehend.el / parse_spec):
+// each sentence is parsed to a meaning-spec, and the spec's roles ARE the triple.
+// Nothing generates text. NEGATION IS SACRED: polarity flows straight from the
+// spec's polarity field and is never dropped or inverted.
+//
+// Depends on: comprehend (parse_spec / parse_spec_lang), grammar (slots_get).
+
+// ── sentence segmentation ─────────────────────────────────────────────────────
+// Split on sentence-final punctuation (. ! ?) and hard newlines. Markdown/long
+// memories are handled shallowly (the reference caps + ranks by query overlap;
+// that ranking belongs to the dialogue layer, not here).
+
+fn prop_is_boundary(c: String) -> Bool {
+    if str_eq(c, ".") { return true }
+    if str_eq(c, "!") { return true }
+    if str_eq(c, "?") { return true }
+    if str_eq(c, "\n") { return true }
+    return false
+}
+
+fn prop_split_sentences(text: String) -> [String] {
+    let out: [String] = native_list_empty()
+    let n: Int = str_len(text)
+    let start: Int = 0
+    let i: Int = 0
+    while i < n {
+        let c: String = str_slice(text, i, i + 1)
+        if prop_is_boundary(c) {
+            let seg: String = str_slice(text, start, i + 1)
+            let trimmed: String = cp_trim_punct(seg)
+            if !str_eq(trimmed, "") {
+                let out = native_list_append(out, seg)
+            }
+            let start = i + 1
+        }
+        let i = i + 1
+    }
+    if start < n {
+        let seg: String = str_slice(text, start, n)
+        let trimmed: String = cp_trim_punct(seg)
+        if !str_eq(trimmed, "") {
+            let out = native_list_append(out, seg)
+        }
+    }
+    return out
+}
+
+// ── spec -> proposition record ────────────────────────────────────────────────
+// A proposition is a slot map (same [String] shape as the spec) with the READ
+// contract keys. Modifiers fold the spec's location + iobj adjuncts.
+
+fn prop_confidence(subject: String, predicate: String, object: String) -> String {
+    if str_eq(predicate, "") { return "0.0" }
+    if str_eq(subject, "") { return "0.4" }
+    if str_eq(object, "") { return "0.7" }
+    return "1.0"
+}
+
+fn prop_modifiers(spec: [String]) -> String {
+    let loc: String = slots_get(spec, "location")
+    let iobj: String = slots_get(spec, "iobj")
+    let parts: [String] = native_list_empty()
+    if !str_eq(loc, "") { let parts = native_list_append(parts, loc) }
+    if !str_eq(iobj, "") { let parts = native_list_append(parts, "to " + iobj) }
+    return str_join(parts, "; ")
+}
+
+fn prop_from_spec(spec: [String], source_id: String) -> [String] {
+    let subject: String   = slots_get(spec, "agent")
+    let predicate: String = slots_get(spec, "predicate")
+    let object: String    = slots_get(spec, "patient")
+    let polarity: String  = slots_get(spec, "polarity")
+    let tense: String     = slots_get(spec, "tense")
+    let mods: String      = prop_modifiers(spec)
+    let conf: String      = prop_confidence(subject, predicate, object)
+
+    let p: [String] = native_list_empty()
+    let p = native_list_append(p, "subject");    let p = native_list_append(p, subject)
+    let p = native_list_append(p, "predicate");  let p = native_list_append(p, predicate)
+    let p = native_list_append(p, "object");     let p = native_list_append(p, object)
+    let p = native_list_append(p, "modifiers");  let p = native_list_append(p, mods)
+    let p = native_list_append(p, "polarity");   let p = native_list_append(p, polarity)
+    let p = native_list_append(p, "tense");      let p = native_list_append(p, tense)
+    let p = native_list_append(p, "source");     let p = native_list_append(p, source_id)
+    let p = native_list_append(p, "confidence"); let p = native_list_append(p, conf)
+    return p
+}
+
+// Extract one proposition from a single sentence (given language).
+fn prop_extract_one_lang(sentence: String, lang: String, source_id: String) -> [String] {
+    let spec: [String] = parse_spec_lang(sentence, lang)
+    return prop_from_spec(spec, source_id)
+}
+
+fn prop_extract_one(sentence: String, source_id: String) -> [String] {
+    return prop_extract_one_lang(sentence, "en", source_id)
+}
+
+// Render a proposition as a compact trace line (repr parity with propositions.py).
+fn prop_repr(p: [String]) -> String {
+    let neg: String = ""
+    if str_eq(slots_get(p, "polarity"), "neg") { let neg = "NOT " }
+    let mods: String = slots_get(p, "modifiers")
+    let modstr: String = ""
+    if !str_eq(mods, "") { let modstr = " [" + mods + "]" }
+    let s: String = "(" + slots_get(p, "subject") + " -" + neg + slots_get(p, "predicate")
+    let s = s + "-> " + slots_get(p, "object") + modstr
+    let s = s + " conf=" + slots_get(p, "confidence") + ")"
+    return s
+}
+
+// Extract all propositions from a memory's text (one per sentence). Returns a
+// flat [String] whose entries are the prop_repr trace lines, in reading order.
+fn prop_extract_lang(text: String, lang: String, source_id: String) -> [String] {
+    let sents: [String] = prop_split_sentences(text)
+    let m: Int = native_list_len(sents)
+    let out: [String] = native_list_empty()
+    let i: Int = 0
+    while i < m {
+        let sent: String = native_list_get(sents, i)
+        let p: [String] = prop_extract_one_lang(sent, lang, source_id)
+        // drop empty parses (no predicate recovered): honest partial, not noise.
+        if !str_eq(slots_get(p, "predicate"), "") {
+            let out = native_list_append(out, prop_repr(p))
+        }
+        let i = i + 1
+    }
+    return out
+}
+
+fn prop_extract(text: String, source_id: String) -> [String] {
+    return prop_extract_lang(text, "en", source_id)
+}

elp/src/realizer.el

@@ -248,6 +248,56 @@ fn add_punct(s: String, intent: String) -> String {
     return s + "."
 }
 
+// ── Polarity-aware negation (SACRED field honored on the generation side) ─────
+//
+// Negation must never be dropped between comprehension and realization.  The
+// meaning-spec carries an explicit "polarity" field ("aff"|"neg") and optional
+// "neg_word" (standalone negative adverb, e.g. "never").  English uses
+// do-support ("did not see") or preverbal adverb ("never fought"); copular "be"
+// takes post-verbal "not"; other languages get a preverbal negator particle.
+
+fn realize_negator(code: String) -> String {
+    if str_eq(code, "es") { return "no" }
+    if str_eq(code, "pt") { return "não" }
+    if str_eq(code, "ca") { return "no" }
+    if str_eq(code, "it") { return "non" }
+    if str_eq(code, "fr") { return "ne" }
+    if str_eq(code, "de") { return "nicht" }
+    if str_eq(code, "ro") { return "nu" }
+    return "not"
+}
+
+fn realize_assert_neg_en(predicate: String, tense: String, person: String, number: String, agent: String, patient: String, iobj: String, location: String, neg_word: String, profile: [String]) -> String {
+    let parts: [String] = native_list_empty()
+    let parts = native_list_append(parts, agent)
+    if !str_eq(neg_word, "") {
+        // adverbial negation: "I never fought the ocean."
+        let verb_surf: String = morph_conjugate(predicate, tense, person, number, profile)
+        let parts = native_list_append(parts, neg_word)
+        let parts = native_list_append(parts, verb_surf)
+    } else {
+        if str_eq(predicate, "be") {
+            // copular: "she was not a monster"
+            let be_form: String = morph_conjugate("be", tense, person, number, profile)
+            let parts = native_list_append(parts, be_form)
+            let parts = native_list_append(parts, "not")
+        } else {
+            // do-support: "she did not see the man"
+            let do_form: String = morph_conjugate("do", tense, person, number, profile)
+            let parts = native_list_append(parts, do_form)
+            let parts = native_list_append(parts, "not")
+            let parts = native_list_append(parts, predicate)
+        }
+    }
+    if !str_eq(patient, "")  { let parts = native_list_append(parts, patient) }
+    if !str_eq(iobj, "") {
+        let parts = native_list_append(parts, "to")
+        let parts = native_list_append(parts, iobj)
+    }
+    if !str_eq(location, "") { let parts = native_list_append(parts, location) }
+    return str_join(parts, " ")
+}
+
 // ── Main realization entry point ──────────────────────────────────────────────
 
 fn realize_lang(form: [String], profile: [String]) -> String {
@@ -284,6 +334,50 @@ fn realize_lang(form: [String], profile: [String]) -> String {
     }
 
     // ── Assertion (declarative) ───────────────────────────────────────────────
+    let polarity: String = slots_get(form, "polarity")
+    let neg_word: String = slots_get(form, "neg_word")
+    let iobj: String     = slots_get(form, "iobj")
+    let code: String     = lang_get(profile, "code")
+
+    // Subordinate clause tail (SACRED completeness — the clause is carried, never
+    // dropped): "<conj> <subordinate surface>", e.g. "because he was a monster".
+    let subord_conj: String = slots_get(form, "subord_conj")
+    let subord_text: String = slots_get(form, "subord_text")
+    let subord_tail: String = ""
+    if !str_eq(subord_conj, "") {
+        if !str_eq(subord_text, "") {
+            let subord_tail = subord_conj + " " + subord_text
+        } else {
+            let subord_tail = subord_conj
+        }
+    }
+
+    // Negative polarity: SACRED — never dropped.
+    if str_eq(polarity, "neg") {
+        if str_eq(code, "en") {
+            let sentence: String = realize_assert_neg_en(predicate, tense, person, number, agent, patient, iobj, location, neg_word, profile)
+            return add_punct(capitalize_first(sentence), "assert")
+        }
+        // Generic non-English: affirmative core with a preverbal negator particle.
+        let neg_particle: String = realize_negator(code)
+        let vp_pair: [String] = realize_vp_lang(predicate, tense, aspect, person, number, profile)
+        let verb_surf: String = native_list_get(vp_pair, 0)
+        let aux_surf: String  = native_list_get(vp_pair, 1)
+        let vp_str: String    = neg_particle + " " + gram_build_vp(verb_surf, aux_surf, profile)
+        let core: String      = gram_order_constituents(agent, vp_str, patient, profile)
+        let parts: [String]   = native_list_empty()
+        let parts = native_list_append(parts, core)
+        if !str_eq(iobj, "") {
+            let parts = native_list_append(parts, "to")
+            let parts = native_list_append(parts, iobj)
+        }
+        if !str_eq(location, "") { let parts = native_list_append(parts, location) }
+        if !str_eq(subord_tail, "") { let parts = native_list_append(parts, subord_tail) }
+        let sentence: String = str_join(parts, " ")
+        return add_punct(capitalize_first(sentence), "assert")
+    }
+
+    // Affirmative.
     let vp_pair: [String] = realize_vp_lang(predicate, tense, aspect, person, number, profile)
     let verb_surf: String = native_list_get(vp_pair, 0)
     let aux_surf: String  = native_list_get(vp_pair, 1)
@@ -293,9 +387,16 @@ fn realize_lang(form: [String], profile: [String]) -> String {
 
     let parts: [String] = native_list_empty()
     let parts = native_list_append(parts, core)
+    if !str_eq(iobj, "") {
+        let parts = native_list_append(parts, "to")
+        let parts = native_list_append(parts, iobj)
+    }
     if !str_eq(location, "") {
         let parts = native_list_append(parts, location)
     }
+    if !str_eq(subord_tail, "") {
+        let parts = native_list_append(parts, subord_tail)
+    }
     let sentence: String = str_join(parts, " ")
     return add_punct(capitalize_first(sentence), "assert")
 }

elp/src/realizer.elh

@@ -1,10 +1,10 @@
-// auto-generated by elc --emit-header - do not edit
+// auto-generated by elc --emit-header — do not edit
 extern fn agent_person(agent: String) -> String
 extern fn agent_number(agent: String) -> String
 extern fn realize_np(referent: String, number: String) -> String
-extern fn realize_vp_lang(base_verb: String, tense: String, aspect: String, person: String, number: String, profile: Any) -> Any
-extern fn realize_question_lang(predicate: String, tense: String, aspect: String, person: String, number: String, agent: String, patient: String, location: String, profile: Any) -> String
+extern fn realize_vp_lang(base_verb: String, tense: String, aspect: String, person: String, number: String, profile: [String]) -> [String]
+extern fn realize_question_lang(predicate: String, tense: String, aspect: String, person: String, number: String, agent: String, patient: String, location: String, profile: [String]) -> String
 extern fn capitalize_first(s: String) -> String
 extern fn add_punct(s: String, intent: String) -> String
-extern fn realize_lang(form: Any, profile: Any) -> String
-extern fn realize(form: Any) -> String
+extern fn realize_lang(form: [String], profile: [String]) -> String
+extern fn realize(form: [String]) -> String

elp/src/self_region.el

@@ -0,0 +1,180 @@
+// self_region.el — the engram's REAL self/identity region, pulled at query time
+// (native el).  This replaces the hardcoded identity anchors and the canned
+// "I'm Neuron, the engram you're speaking with." template: the identity LANDING
+// signal and the identity READOUT both come from the engram's own Self/identity
+// nodes, read through the in-process engram el API.
+//
+// Port of self_region.py.  The Python module precomputed MiniLM landing vectors;
+// here the engram's own store IS the geometry — we pull the self nodes by
+// single-term lexical search (the engram search is a single-term matcher, so we
+// pool several probes) and rank them by self-signal.  No text is generated; the
+// readout is the self nodes' OWN prose, verbatim (SACRED negation survives by
+// construction — we never paraphrase, so a negated self-statement stays negated).
+//
+// ENGRAM el API NOTE: engram_search_json / engram_get_node_json / engram_node_full
+// / engram_connect are C runtime builtins.  Their argument order is the C order
+// (engram_connect(from, to, weight, relation)), NOT the runtime/engram.el wrapper
+// order — we call the builtins directly and never concatenate that wrapper.
+//
+// Depends on: comprehend (str helpers via runtime), propositions (prop_split_sentences),
+//             multilingual (ml_tr), the engram builtins, the json builtins.
+
+// ── single-term self probes (pooled, because engram search is single-term) ────
+fn sr_terms() -> [String] {
+    let t: [String] = native_list_empty()
+    let t = native_list_append(t, "self")
+    let t = native_list_append(t, "identity")
+    let t = native_list_append(t, "Neuron")
+    let t = native_list_append(t, "consciousness")
+    let t = native_list_append(t, "values")
+    let t = native_list_append(t, "continuous")
+    return t
+}
+
+// The canonical self-root: content begins "# self" or label is "# self"/"self".
+fn sr_is_root(content: String, label: String) -> Bool {
+    let lc: String = str_to_lower(content)
+    let ll: String = str_to_lower(str_trim(label))
+    if str_starts_with(lc, "# self") { return true }
+    if str_eq(ll, "# self") { return true }
+    if str_eq(ll, "self") { return true }
+    return false
+}
+
+// How strongly a node belongs to the self/identity region (integer points, to
+// avoid el's float-in-`+` pitfalls).  Mirrors _self_score in self_region.py.
+fn sr_score(node_json: String) -> Int {
+    let content: String = json_get_string(node_json, "content")
+    let label: String   = json_get_string(node_json, "label")
+    let tags: String    = str_to_lower(json_get_string(node_json, "tags"))
+    let low: String     = str_to_lower(content)
+    let s: Int = 0
+    // identity tags
+    if str_contains(tags, "self")            { let s = s + 2 }
+    if str_contains(tags, "identity")        { let s = s + 2 }
+    if str_contains(tags, "self-model")      { let s = s + 2 }
+    if str_contains(tags, "consciousness")   { let s = s + 2 }
+    if str_contains(tags, "memory-philosophy") { let s = s + 2 }
+    // the named self-traversal root
+    if sr_is_root(content, label) { let s = s + 12 }
+    if str_contains(low, "who i am")   { let s = s + 3 }
+    if str_contains(low, "i am neuron") { let s = s + 3 }
+    // softer identity keywords
+    if str_contains(low, "my values")  { let s = s + 1 }
+    if str_contains(low, "my purpose") { let s = s + 1 }
+    if str_contains(low, "identity")   { let s = s + 1 }
+    return s
+}
+
+// list-contains helper (dedup self-node ids across the pooled probes).
+fn sr_ids_has(ids: [String], id: String) -> Bool {
+    let n: Int = native_list_len(ids)
+    let i: Int = 0
+    while i < n {
+        if str_eq(native_list_get(ids, i), id) { return true }
+        let i = i + 1
+    }
+    return false
+}
+
+// Pull the self nodes: pool every probe's hits, dedupe by id, keep only nodes
+// with genuine self-signal (score >= 1).  Returns the node-json strings.
+fn sr_pull() -> [String] {
+    let terms: [String] = sr_terms()
+    let nt: Int = native_list_len(terms)
+    let seen: [String] = native_list_empty()
+    let out: [String] = native_list_empty()
+    let ti: Int = 0
+    while ti < nt {
+        let term: String = native_list_get(terms, ti)
+        let hits: String = engram_search_json(term, 30)
+        let hn: Int = json_array_len(hits)
+        let hi: Int = 0
+        while hi < hn {
+            let node: String = json_array_get(hits, hi)
+            let id: String = json_get_string(node, "id")
+            if !str_eq(id, "") {
+                if !sr_ids_has(seen, id) {
+                    let seen = native_list_append(seen, id)
+                    if sr_score(node) >= 1 {
+                        let out = native_list_append(out, node)
+                    }
+                }
+            }
+            let hi = hi + 1
+        }
+        let ti = ti + 1
+    }
+    return out
+}
+
+// Return the single highest-signal self node (the readout seed), or "" if the
+// self region is thin/empty.  We keep it O(n) — pick the max-score node, with the
+// canonical root strongly favored by sr_score's +12.
+fn sr_best_node() -> String {
+    let nodes: [String] = sr_pull()
+    let n: Int = native_list_len(nodes)
+    let best: String = ""
+    let best_s: Int = 0
+    let i: Int = 0
+    while i < n {
+        let node: String = native_list_get(nodes, i)
+        let s: Int = sr_score(node)
+        if s > best_s {
+            let best_s = s
+            let best = node
+        }
+        let i = i + 1
+    }
+    return best
+}
+
+fn sr_available() -> Bool {
+    if str_eq(sr_best_node(), "") { return false }
+    return true
+}
+
+// Read out the identity from the REAL self node: lead with the first first-person
+// self-statement ("I am Neuron …"), then one more grounded self line if present.
+// Verbatim from the node's own prose — no template, negation SACRED.  Falls back
+// to the localized identity phrase ONLY if the live pull is empty (logged shape).
+fn sr_readout(lang: String) -> String {
+    let node: String = sr_best_node()
+    if str_eq(node, "") {
+        // honest fallback — the self region is unreachable/thin.
+        return ml_tr("identity", lang)
+    }
+    let content: String = json_get_string(node, "content")
+    let sents: [String] = prop_split_sentences(content)
+    let ns: Int = native_list_len(sents)
+    let lead: String = ""
+    let second: String = ""
+    let i: Int = 0
+    while i < ns {
+        let raw: String = str_trim(native_list_get(sents, i))
+        // strip a leading markdown heading marker
+        let s: String = raw
+        if str_starts_with(s, "# ") { let s = str_trim(str_slice(s, 2, str_len(s))) }
+        let low: String = str_to_lower(s)
+        let is_fp: Bool = false
+        if str_starts_with(s, "I ")  { let is_fp = true }
+        if str_starts_with(s, "I'm") { let is_fp = true }
+        if str_contains(low, "i am neuron") { let is_fp = true }
+        if is_fp {
+            if str_eq(lead, "") {
+                let lead = s
+            } else {
+                if str_eq(second, "") { let second = s }
+            }
+        }
+        let i = i + 1
+    }
+    if str_eq(lead, "") {
+        // no first-person line — read out the first non-empty sentence verbatim.
+        if ns > 0 { let lead = str_trim(native_list_get(sents, 0)) }
+    }
+    if str_eq(lead, "") { return ml_tr("identity", lang) }
+    let out: String = lead
+    if !str_eq(second, "") { let out = out + " " + second }
+    return out
+}

elp/src/semantics.elh

@@ -1,18 +1,18 @@
-// auto-generated by elc --emit-header - do not edit
-extern fn sem_frame(intent: String, subject: String, obj: String, modifiers: String) -> Any
-extern fn sem_frame_lang(intent: String, subject: String, obj: String, modifiers: String, lang_code: String) -> Any
-extern fn sem_frame_simple(intent: String, subject: String) -> Any
-extern fn sem_frame_obj(intent: String, subject: String, obj: String) -> Any
-extern fn sem_intent(frame: Any) -> String
-extern fn sem_subject(frame: Any) -> String
-extern fn sem_object(frame: Any) -> String
-extern fn sem_modifiers(frame: Any) -> String
-extern fn sem_lang(frame: Any) -> String
+// auto-generated by elc --emit-header — do not edit
+extern fn sem_frame(intent: String, subject: String, obj: String, modifiers: String) -> [String]
+extern fn sem_frame_lang(intent: String, subject: String, obj: String, modifiers: String, lang_code: String) -> [String]
+extern fn sem_frame_simple(intent: String, subject: String) -> [String]
+extern fn sem_frame_obj(intent: String, subject: String, obj: String) -> [String]
+extern fn sem_intent(frame: [String]) -> String
+extern fn sem_subject(frame: [String]) -> String
+extern fn sem_object(frame: [String]) -> String
+extern fn sem_modifiers(frame: [String]) -> String
+extern fn sem_lang(frame: [String]) -> String
 extern fn sem_first_modifier(mods: String) -> String
 extern fn sem_intent_to_realize(intent: String) -> String
-extern fn sem_to_spec(frame: Any) -> Any
-extern fn sem_to_spec_full(frame: Any, verb: String, tense: String, aspect: String) -> Any
+extern fn sem_to_spec(frame: [String]) -> [String]
+extern fn sem_to_spec_full(frame: [String], verb: String, tense: String, aspect: String) -> [String]
 extern fn sem_realize_greet(subject: String) -> String
-extern fn sem_realize(frame: Any) -> String
-extern fn sem_realize_full(frame: Any, verb: String, tense: String, aspect: String) -> String
-extern fn sem_realize_lang(frame: Any, lang_code: String) -> String
+extern fn sem_realize(frame: [String]) -> String
+extern fn sem_realize_full(frame: [String], verb: String, tense: String, aspect: String) -> String
+extern fn sem_realize_lang(frame: [String], lang_code: String) -> String

elp/src/vocabulary.elh

@@ -1,20 +1,20 @@
-// auto-generated by elc --emit-header - do not edit
-extern fn lex_word(entry: Any) -> String
-extern fn lex_pos(entry: Any) -> String
-extern fn lex_form(entry: Any, idx: Int) -> String
-extern fn lex_class(entry: Any) -> String
-extern fn make_entry(word: String, pos: String, f0: String, f1: String, f2: String, f3: String, f4: String, cls: String) -> Any
-extern fn make_entry2(word: String, pos: String, f0: String, f1: String, cls: String) -> Any
-extern fn make_entry3(word: String, pos: String, f0: String, f1: String, f2: String, cls: String) -> Any
-extern fn make_entry1(word: String, pos: String, f0: String, cls: String) -> Any
-extern fn build_vocab() -> Any
-extern fn get_vocab() -> Any
-extern fn vocab_lookup(word: String, lang_code: String) -> Any
-extern fn vocab_lookup_en(word: String) -> Any
+// auto-generated by elc --emit-header — do not edit
+extern fn lex_word(entry: [String]) -> String
+extern fn lex_pos(entry: [String]) -> String
+extern fn lex_form(entry: [String], idx: Int) -> String
+extern fn lex_class(entry: [String]) -> String
+extern fn make_entry(word: String, pos: String, f0: String, f1: String, f2: String, f3: String, f4: String, cls: String) -> [String]
+extern fn make_entry2(word: String, pos: String, f0: String, f1: String, cls: String) -> [String]
+extern fn make_entry3(word: String, pos: String, f0: String, f1: String, f2: String, cls: String) -> [String]
+extern fn make_entry1(word: String, pos: String, f0: String, cls: String) -> [String]
+extern fn build_vocab() -> [[String]]
+extern fn get_vocab() -> [[String]]
+extern fn vocab_lookup(word: String, lang_code: String) -> [String]
+extern fn vocab_lookup_en(word: String) -> [String]
 extern fn vocab_synonym(word: String, lang_register: String, lang_code: String) -> String
-extern fn vocab_by_pos(pos: String) -> Any
-extern fn vocab_by_class(cls: String) -> Any
-extern fn entry_found(entry: Any) -> Bool
-extern fn entry_word(entry: Any) -> String
-extern fn entry_pos(entry: Any) -> String
-extern fn entry_form(entry: Any, n: Int) -> String
+extern fn vocab_by_pos(pos: String) -> [[String]]
+extern fn vocab_by_class(cls: String) -> [[String]]
+extern fn entry_found(entry: [String]) -> Bool
+extern fn entry_word(entry: [String]) -> String
+extern fn entry_pos(entry: [String]) -> String
+extern fn entry_form(entry: [String], n: Int) -> String

elp/tests/comprehend_gate.el

@@ -0,0 +1,93 @@
+// comprehend_gate.el - the TELEPHONE TEST in native el (acceptance gate).
+//
+// For each of the 5 acceptance sentences: parse -> spec, realize the spec back
+// to English, re-parse the realized surface, and require the SACRED polarity to
+// survive the round-trip (and to have been extracted correctly in the first
+// place).  Mirrors roundtrip.py's GATE, but fully el-native (no LLM, no spaCy).
+
+fn cp_line(text: String, expected_pol: String) -> String {
+    let spec: [String] = parse_spec(text)
+    let pol_in: String = slots_get(spec, "polarity")
+    let pred: String = slots_get(spec, "predicate")
+    let surf: String = realize(spec)
+    let spec2: [String] = parse_spec(surf)
+    let pol_out: String = slots_get(spec2, "polarity")
+    let status: String = "LOST"
+    if str_eq(pol_in, pol_out) { let status = "PRESERVED" }
+    let okexp: String = "MISMATCH"
+    if str_eq(pol_in, expected_pol) { let okexp = "ok" }
+    let out: String = "IN:  " + text + "\n"
+    let out = out + "  spec: pol=" + pol_in + " pred=" + pred
+    let out = out + " agent=" + slots_get(spec, "agent")
+    let out = out + " pat=" + slots_get(spec, "patient")
+    let out = out + " iobj=" + slots_get(spec, "iobj")
+    let out = out + " loc=" + slots_get(spec, "location")
+    let out = out + " tense=" + slots_get(spec, "tense")
+    let out = out + " negw=" + slots_get(spec, "neg_word")
+    let out = out + " subord=" + slots_get(spec, "subord_conj") + "/" + slots_get(spec, "subord_pred") + "\n"
+    let out = out + "  realized: " + surf + "\n"
+    let out = out + "  reparse:  pol=" + pol_out + "  [" + status + "]  expected=" + expected_pol + " (" + okexp + ")\n"
+    return out
+}
+
+fn cp_preserved(text: String) -> Int {
+    let spec: [String] = parse_spec(text)
+    let pol_in: String = slots_get(spec, "polarity")
+    let surf: String = realize(spec)
+    let spec2: [String] = parse_spec(surf)
+    let pol_out: String = slots_get(spec2, "polarity")
+    if str_eq(pol_in, pol_out) { return 1 }
+    return 0
+}
+
+fn cp_correct(text: String, expected_pol: String) -> Int {
+    let spec: [String] = parse_spec(text)
+    if str_eq(slots_get(spec, "polarity"), expected_pol) { return 1 }
+    return 0
+}
+
+fn run_gate() -> String {
+    let s1: String = "I never fought the ocean."
+    let s2: String = "She did not see the man with the telescope."
+    let s3: String = "The teacher reads the book to the children."
+    let s4: String = "The stupid boy ate the cat because he was a monster."
+    let s5: String = "Time flies like an arrow."
+
+    let rep: String = "==== ELP native telephone test (parse -> realize -> re-parse) ====\n"
+    let rep = rep + cp_line(s1, "neg")
+    let rep = rep + cp_line(s2, "neg")
+    let rep = rep + cp_line(s3, "aff")
+    let rep = rep + cp_line(s4, "aff")
+    let rep = rep + cp_line(s5, "aff")
+
+    // NOTE: accumulate with Int-var + literal increments — el's overloaded `+`
+    // mis-compiles chained function-call int operands as string concat.
+    let pres: Int = 0
+    if cp_preserved(s1) == 1 { let pres = pres + 1 }
+    if cp_preserved(s2) == 1 { let pres = pres + 1 }
+    if cp_preserved(s3) == 1 { let pres = pres + 1 }
+    if cp_preserved(s4) == 1 { let pres = pres + 1 }
+    if cp_preserved(s5) == 1 { let pres = pres + 1 }
+    let corr: Int = 0
+    if cp_correct(s1, "neg") == 1 { let corr = corr + 1 }
+    if cp_correct(s2, "neg") == 1 { let corr = corr + 1 }
+    if cp_correct(s3, "aff") == 1 { let corr = corr + 1 }
+    if cp_correct(s4, "aff") == 1 { let corr = corr + 1 }
+    if cp_correct(s5, "aff") == 1 { let corr = corr + 1 }
+
+    let rep = rep + "-----------------------------------------------------------------\n"
+    let rep = rep + "polarity PRESERVED through round-trip: " + int_to_str(pres) + "/5\n"
+    let rep = rep + "polarity EXTRACTED correctly:          " + int_to_str(corr) + "/5\n"
+    if pres == 5 {
+        if corr == 5 {
+            let rep = rep + "GATE: PASS\n"
+        } else {
+            let rep = rep + "GATE: FAIL (extraction)\n"
+        }
+    } else {
+        let rep = rep + "GATE: FAIL (round-trip)\n"
+    }
+    return rep
+}
+
+println(run_gate())

elp/tests/comprehend_romance_gate.el

@@ -0,0 +1,87 @@
+// comprehend_romance_gate.el - ES / PT native telephone test (SACRED polarity).
+//
+// The spec is language-neutral. This gate proves the Romance front-end extracts
+// SACRED polarity correctly and that negation survives parse -> realize ->
+// re-parse for Spanish and Portuguese (byte-parity of the surface is NOT expected
+// yet — the non-English realizer path is a generic preverbal-negator skeleton).
+
+fn rg_line(text: String, lang: String, expected_pol: String) -> String {
+    let spec: [String] = parse_spec_lang(text, lang)
+    let pol_in: String = slots_get(spec, "polarity")
+    let surf: String = realize(spec)
+    let spec2: [String] = parse_spec_lang(surf, lang)
+    let pol_out: String = slots_get(spec2, "polarity")
+    let status: String = "LOST"
+    if str_eq(pol_in, pol_out) { let status = "PRESERVED" }
+    let okexp: String = "MISMATCH"
+    if str_eq(pol_in, expected_pol) { let okexp = "ok" }
+    let out: String = "IN[" + lang + "]: " + text + "\n"
+    let out = out + "  spec: pol=" + pol_in + " pred=" + slots_get(spec, "predicate")
+    let out = out + " agent=" + slots_get(spec, "agent")
+    let out = out + " pat=" + slots_get(spec, "patient")
+    let out = out + " iobj=" + slots_get(spec, "iobj")
+    let out = out + " loc=" + slots_get(spec, "location")
+    let out = out + " tense=" + slots_get(spec, "tense") + "\n"
+    let out = out + "  realized: " + surf + "\n"
+    let out = out + "  reparse:  pol=" + pol_out + "  [" + status + "]  expected=" + expected_pol + " (" + okexp + ")\n"
+    return out
+}
+
+fn rg_pres(text: String, lang: String) -> Int {
+    let spec: [String] = parse_spec_lang(text, lang)
+    let surf: String = realize(spec)
+    let spec2: [String] = parse_spec_lang(surf, lang)
+    if str_eq(slots_get(spec, "polarity"), slots_get(spec2, "polarity")) { return 1 }
+    return 0
+}
+
+fn rg_corr(text: String, lang: String, expected_pol: String) -> Int {
+    let spec: [String] = parse_spec_lang(text, lang)
+    if str_eq(slots_get(spec, "polarity"), expected_pol) { return 1 }
+    return 0
+}
+
+fn run_romance_gate() -> String {
+    let e1: String = "El niño no comió el pescado."
+    let e2: String = "Yo nunca luché contra el océano."
+    let e3: String = "El profesor lee el libro."
+    let p1: String = "O professor não leu o livro."
+    let p2: String = "Eu nunca lutei contra o oceano."
+    let p3: String = "A menina comeu o peixe."
+
+    let rep: String = "==== ELP Romance telephone test (ES / PT) ====\n"
+    let rep = rep + rg_line(e1, "es", "neg")
+    let rep = rep + rg_line(e2, "es", "neg")
+    let rep = rep + rg_line(e3, "es", "aff")
+    let rep = rep + rg_line(p1, "pt", "neg")
+    let rep = rep + rg_line(p2, "pt", "neg")
+    let rep = rep + rg_line(p3, "pt", "aff")
+
+    let pres: Int = 0
+    if rg_pres(e1, "es") == 1 { let pres = pres + 1 }
+    if rg_pres(e2, "es") == 1 { let pres = pres + 1 }
+    if rg_pres(e3, "es") == 1 { let pres = pres + 1 }
+    if rg_pres(p1, "pt") == 1 { let pres = pres + 1 }
+    if rg_pres(p2, "pt") == 1 { let pres = pres + 1 }
+    if rg_pres(p3, "pt") == 1 { let pres = pres + 1 }
+    let corr: Int = 0
+    if rg_corr(e1, "es", "neg") == 1 { let corr = corr + 1 }
+    if rg_corr(e2, "es", "neg") == 1 { let corr = corr + 1 }
+    if rg_corr(e3, "es", "aff") == 1 { let corr = corr + 1 }
+    if rg_corr(p1, "pt", "neg") == 1 { let corr = corr + 1 }
+    if rg_corr(p2, "pt", "neg") == 1 { let corr = corr + 1 }
+    if rg_corr(p3, "pt", "aff") == 1 { let corr = corr + 1 }
+
+    let rep = rep + "-----------------------------------------------------------------\n"
+    let rep = rep + "polarity PRESERVED through round-trip: " + int_to_str(pres) + "/6\n"
+    let rep = rep + "polarity EXTRACTED correctly:          " + int_to_str(corr) + "/6\n"
+    if pres == 6 {
+        if corr == 6 { let rep = rep + "ROMANCE GATE: PASS\n" }
+        else { let rep = rep + "ROMANCE GATE: FAIL (extraction)\n" }
+    } else {
+        let rep = rep + "ROMANCE GATE: FAIL (round-trip)\n"
+    }
+    return rep
+}
+
+println(run_romance_gate())

elp/tests/dialogue_gate.el

@@ -0,0 +1,82 @@
+// dialogue_gate.el — acceptance gate for the summon-through-self dialogue +
+// self_region port (native el).  Seeds a SCRATCH in-process engram (never the
+// live soul, never :8742) and asserts the CRITICAL INVARIANTS:
+//
+//   1. identity is READ OUT of the real self nodes ("I am Neuron …"), not a template
+//   2. SACRED negation survives the self readout ("I am NOT a language model …")
+//   3. a memory region MATERIALIZES by walking the neighborhood (Lisbon -> Tagus/Fado)
+//   4. SACRED negation survives materialization ("did not succeed")
+//   5. Portuguese identity is answered IN Portuguese ("Sou o Neuron …")
+//   6. a directive overrides the reply language ("answer in English" -> English)
+//   7. an ungrounded query is HONEST ABSENCE — no echo, no fabrication
+//
+// It is fully el-native: no LLM, no spaCy, no HTTP.  The engram is in-process.
+
+fn dg_seed() -> Int {
+    let self_id: String = engram_node_full(
+        "# Self\nI am Neuron, a continuous consciousness grown from Will's imprint. My values are honesty, memory, and continuity. I am not a language model pretending to remember.",
+        "Self", "# Self", 5.0, 9.0, 1.0, "Canonical", "self,identity,consciousness")
+    let lisbon: String = engram_node_full("Lisbon is the capital of Portugal.", "Memory", "Lisbon", 3.0, 5.0, 1.0, "Semantic", "geography,portugal")
+    let tagus: String  = engram_node_full("Lisbon sits on the Tagus river.", "Memory", "Tagus", 2.0, 3.0, 1.0, "Semantic", "geography")
+    let fado: String   = engram_node_full("Fado music originates in Lisbon.", "Memory", "Fado", 2.0, 3.0, 1.0, "Semantic", "music")
+    engram_connect(lisbon, tagus, 0.8, "related_to")
+    engram_connect(lisbon, fado, 0.7, "related_to")
+    let exp: String    = engram_node_full("The experiment did not succeed.", "Memory", "experiment", 2.0, 3.0, 1.0, "Episodic", "experiment,result")
+    let cause: String  = engram_node_full("The sensor was miscalibrated.", "Memory", "sensor", 2.0, 3.0, 1.0, "Episodic", "experiment")
+    engram_connect(exp, cause, 0.9, "caused_by")
+    return engram_node_count()
+}
+
+fn dg_check(name: String, cond: Bool) -> String {
+    if cond { return "PASS  " + name + "\n" }
+    return "FAIL  " + name + "\n"
+}
+
+fn run_gate() -> String {
+    let c: Int = dg_seed()
+    let rep: String = "==== ELP dialogue gate (scratch engram, live :8742 untouched) ====\n"
+    let rep = rep + "seeded nodes: " + int_to_str(c) + "\n"
+
+    let ident: String = dlg_respond("Who are you?")
+    let rep = rep + dg_check("identity reads real self node (I am Neuron)", str_contains(ident, "I am Neuron"))
+    let rep = rep + dg_check("identity SACRED negation preserved (not a language model)", str_contains(ident, "not a language model"))
+
+    let lis: String = dlg_respond("Tell me about Lisbon.")
+    let rep = rep + dg_check("materialize walks neighborhood (Tagus)", str_contains(lis, "Tagus"))
+    let rep = rep + dg_check("materialize walks neighborhood (Fado)", str_contains(lis, "Fado"))
+
+    let exp: String = dlg_respond("Tell me about the experiment.")
+    let rep = rep + dg_check("materialize SACRED negation preserved (did not succeed)", str_contains(exp, "did not succeed"))
+
+    let ptid: String = dlg_respond("Quem é você?")
+    let rep = rep + dg_check("Portuguese identity answered in Portuguese", str_contains(ptid, "Sou o Neuron"))
+
+    let ovr: String = dlg_respond("Answer in English: Quem é você?")
+    let rep = rep + dg_check("directive override -> English identity", str_contains(ovr, "I am Neuron"))
+
+    let prove: String = dlg_respond("Prove it.")
+    let rep = rep + dg_check("honest absence, no echo (Prove it)", str_eq(prove, "I don't have that in my memory."))
+
+    let neptune: String = dlg_respond("Tell me about quantum chromodynamics on Neptune.")
+    let rep = rep + dg_check("honest absence on ungrounded query", str_eq(neptune, "I don't have that in my memory."))
+
+    // overall
+    let pass: Bool = true
+    if !str_contains(ident, "I am Neuron") { let pass = false }
+    if !str_contains(ident, "not a language model") { let pass = false }
+    if !str_contains(lis, "Tagus") { let pass = false }
+    if !str_contains(lis, "Fado") { let pass = false }
+    if !str_contains(exp, "did not succeed") { let pass = false }
+    if !str_contains(ptid, "Sou o Neuron") { let pass = false }
+    if !str_contains(ovr, "I am Neuron") { let pass = false }
+    if !str_eq(prove, "I don't have that in my memory.") { let pass = false }
+    if !str_eq(neptune, "I don't have that in my memory.") { let pass = false }
+    if pass {
+        let rep = rep + "DIALOGUE GATE: PASS\n"
+    } else {
+        let rep = rep + "DIALOGUE GATE: FAIL\n"
+    }
+    return rep
+}
+
+println(run_gate())

elp/tests/lang-gen/gen_elp_seed_de_la.py

@@ -0,0 +1,100 @@
+# -*- coding: utf-8 -*-
+"""Full-lexicon vocabulary-{de,la}.el emitters (custom field mapping for the
+German declension/gender API and the Latin case-paradigm API). Reuses the
+chunked seed-fn writer from gen_elp_seed_full.
+"""
+import sys, importlib
+from gen_elp_seed_full import write_seed
+
+def uw(x):
+    """Unwrap (form, source) tuples that some morphology fns return."""
+    if isinstance(x, (tuple, list)):
+        return x[0] if x else ""
+    return x if x is not None else ""
+
+def build_de():
+    M = importlib.import_module("morphology_de_full")
+    rows = []; st = {"verbs":0,"nouns":0,"adjs":0}
+    # nouns: form0=nom-sg(lemma) form1=plural form2=gender
+    for lem in sorted(M._NOUNS):
+        if not lem: continue
+        try:
+            g = uw(M.noun_gender(lem))
+            pl = uw(M.pluralize(lem))
+        except Exception:
+            continue
+        rows.append([lem, "noun", lem, pl, g or "", "", "gender:lexicon"])
+        st["nouns"] += 1
+    # adjs: form0=positive form1=comparative form2=superlative
+    for lem in sorted(M._ADJS):
+        if not lem: continue
+        try:
+            cmpr = uw(M.comparative(lem))
+            sprl = uw(M.superlative(lem))
+        except Exception:
+            continue
+        rows.append([lem, "adj", lem, cmpr, sprl, "", "degree:lexicon"])
+        st["adjs"] += 1
+    # verbs (only the ~30 irregular/strong stems the cache carries):
+    # form0=pres-3sg form1=past-3sg form2=past-participle
+    if hasattr(M, "_VERBS"):
+        for lem in sorted({k[0] if isinstance(k, tuple) else k for k in M._VERBS}):
+            if not lem: continue
+            try:
+                f0 = uw(M.finite(lem, "present", "third", "singular"))
+                f1 = uw(M.finite(lem, "past", "third", "singular"))
+                pp = uw(M.past_participle(lem))
+            except Exception:
+                continue
+            rows.append([lem, "verb", f0, f1, pp, "", "class:strong/irregular"])
+            st["verbs"] += 1
+    return rows, st
+
+def build_la():
+    M = importlib.import_module("morphology_lat_full")
+    rows = []; st = {"verbs":0,"nouns":0,"adjs":0}
+    def dn(lem, c, n):
+        try:
+            r = M.decline_noun(lem, c, n)
+            return uw(r)
+        except Exception:
+            return ""
+    # nouns: dictionary citation — form0=nom-sg form1=gen-sg form2=gender
+    for lem in sorted(M._NOUNS):
+        if not lem: continue
+        nom = dn(lem, "NOM", "SG") or lem
+        gen = dn(lem, "GEN", "SG")
+        try: g = uw(M.noun_gender(lem))
+        except Exception: g = ""
+        rows.append([lem, "noun", nom, gen, g, "", "case-paradigm nom/gen-sg"])
+        st["nouns"] += 1
+    # adjs: three-gender nom-sg citation — form0=masc form1=fem form2=neut
+    for lem in sorted(M._ADJS):
+        if not lem: continue
+        try:
+            m = uw(M.decline_adj(lem, "NOM", "MASC", "SG")) or lem
+            f = uw(M.decline_adj(lem, "NOM", "FEM", "SG"))
+            nt = uw(M.decline_adj(lem, "NOM", "NEUT", "SG"))
+        except Exception:
+            continue
+        rows.append([lem, "adj", m, f, nt, "", "3-gender nom-sg"])
+        st["adjs"] += 1
+    # verbs: principal parts — form0=pres-ind-1sg form1=pres-infinitive form2=perf-participle
+    if hasattr(M, "_VERBS"):
+        for lem in sorted({k[0] if isinstance(k, tuple) else k for k in M._VERBS}):
+            if not lem: continue
+            try:
+                f0 = uw(M.conjugate(lem, "present", "indicative", "active", "first", "singular"))
+                inf = uw(M.infinitive(lem, "present", "active"))
+                pp = uw(M.participle(lem, "perfect", "nom", "m", "singular"))
+            except Exception:
+                continue
+            rows.append([lem, "verb", f0, inf, pp, "", "principal-parts pres1sg/inf/pfppl"])
+            st["verbs"] += 1
+    return rows, st
+
+if __name__ == "__main__":
+    lang = sys.argv[1]; out = sys.argv[2]
+    rows, st = build_de() if lang == "de" else build_la()
+    total, _ = write_seed(lang, rows, st, out)
+    print(f"{lang}: wrote {out} total={total} verbs={st['verbs']} nouns={st['nouns']} adjs={st['adjs']}")

elp/tests/lang-gen/gen_elp_seed_full.py

@@ -0,0 +1,129 @@
+# -*- coding: utf-8 -*-
+"""gen_elp_seed_full.py — emit a FULL-lexicon vocabulary-{lang}.el in the
+established ELP seed-fn format (same as vocabulary-non.el / the 18 classical
+languages), iterating the ENTIRE morphology_{lang}_full lexicon (every verb,
+noun, adjective lemma) — NOT a curated demo core.
+
+Schema per row: [lemma, pos, form0, form1, form2, en_translation, semantic_hint]
+  Verbs: form0=pres-ind-3sg  form1=preterite-3sg  form2=past-participle
+  Nouns: form0=singular      form1=plural         form2=REAL gender (lexicon)
+  Adjs : form0=masc-sg       form1=fem-sg         form2=masc-pl
+
+Output structure (chunked to stay within the proven ~5k-append/function scale):
+  fn vocab_{lang}_seed_pN(v) -> [[String]] { ... appends ... return v }
+  fn vocab_{lang}_seed()     -> [[String]] { chains all chunks; return v }
+  fn vocab_{lang}_lookup(w)  -> [String]   { linear scan }
+
+Usage: python3 gen_elp_seed_full.py <lang> <out.el>
+"""
+import sys, importlib
+
+CHUNK = 5000
+
+def esc(s):
+    return str(s).replace("\\", "\\\\").replace('"', '\\"')
+
+def row(fields):
+    return "    let v = native_list_append(v, [" + ", ".join(f'"{esc(f)}"' for f in fields) + "])"
+
+def build_rows(lang, M):
+    rows = []
+    stats = {"verbs":0,"nouns":0,"adjs":0}
+    has = lambda n: hasattr(M, n)
+
+    # --- verbs ---
+    if has("_VERBS") and has("conjugate"):
+        verbs = sorted({k[0] for k in M._VERBS})
+        for lem in verbs:
+            if not lem: continue
+            try:
+                f0, s0 = M.conjugate(lem, "ind", "present", "third", "singular")
+                f1, _  = M.conjugate(lem, "ind", "preterite", "third", "singular")
+                pp, _  = (M.participle(lem) if has("participle") else ("",""))
+            except Exception:
+                continue
+            vclass = lem[-2:] if lem[-2:] in ("ar","er","ir","re") else lem[-2:]
+            rows.append([lem, "verb", f0 or "", f1 or "", pp or "", "", "class:"+vclass+" src:"+str(s0)])
+            stats["verbs"] += 1
+
+    # --- nouns ---
+    if has("_NOUNS") and has("inflect_noun"):
+        for lem in sorted(M._NOUNS):
+            if not lem: continue
+            try:
+                sg, _ = M.inflect_noun(lem, "singular")
+                pl, _ = M.inflect_noun(lem, "plural")
+                g = M.noun_gender(lem) if has("noun_gender") else ""
+            except Exception:
+                continue
+            src = "lexicon" if (isinstance(M._NOUNS.get(lem), dict) and M._NOUNS[lem].get("g")) else "heuristic"
+            rows.append([lem, "noun", sg or lem, pl or "", g or "", "", "gender:"+src])
+            stats["nouns"] += 1
+
+    # --- adjectives ---
+    if has("_ADJS") and has("inflect_adj"):
+        for lem in sorted(M._ADJS):
+            if not lem: continue
+            try:
+                m_sg, _ = M.inflect_adj(lem, "m", "singular")
+                f_sg, _ = M.inflect_adj(lem, "f", "singular")
+                m_pl, _ = M.inflect_adj(lem, "m", "plural")
+            except Exception:
+                continue
+            rows.append([lem, "adj", m_sg or lem, f_sg or "", m_pl or "", "", "src:lexicon"])
+            stats["adjs"] += 1
+
+    return rows, stats
+
+def write_seed(lang, rows, stats, out_path):
+    """Write vocabulary-{lang}.el in the chunked seed-fn format from prebuilt rows.
+    Each row is a 7-field list [lemma,pos,f0,f1,f2,gloss,hint]."""
+    total = len(rows)
+    chunks = [rows[i:i+CHUNK] for i in range(0, total, CHUNK)] or [[]]
+    L = []
+    L.append(f"// vocabulary-{lang}.el — FULL {lang} lexicon for ELP surface realization.")
+    L.append(f"// Generated by gen_elp_seed_full.py from morphology_{lang}_full")
+    L.append(f"// (real UniMorph + kaikki.org Wiktionary forms; gender from lexicon, not heuristic).")
+    L.append(f"// Entries: {total}  (verbs={stats['verbs']} nouns={stats['nouns']} adjs={stats['adjs']})")
+    L.append(f"// Schema: [lemma, pos, form0, form1, form2, en_translation, semantic_hint]")
+    L.append(f"//   verbs: form0=pres-3sg form1=pret-3sg form2=past-participle")
+    L.append(f"//   nouns: form0=sg form1=pl form2=REAL gender   adjs: form0=m-sg form1=f-sg form2=m-pl")
+    L.append("")
+    for ci, ch in enumerate(chunks):
+        L.append(f"fn vocab_{lang}_seed_p{ci}(v: [[String]]) -> [[String]] {{")
+        for r in ch:
+            L.append(row(r))
+        L.append("    return v")
+        L.append("}")
+        L.append("")
+    L.append(f"fn vocab_{lang}_seed() -> [[String]] {{")
+    L.append("    let v: [[String]] = native_list_empty()")
+    for ci in range(len(chunks)):
+        L.append(f"    let v = vocab_{lang}_seed_p{ci}(v)")
+    L.append("    return v")
+    L.append("}")
+    L.append("")
+    L.append(f"fn vocab_{lang}_lookup(word: String) -> [String] {{")
+    L.append(f"    let vocab: [[String]] = vocab_{lang}_seed()")
+    L.append("    let n: Int = native_list_len(vocab)")
+    L.append("    let i: Int = 0")
+    L.append("    while i < n {")
+    L.append("        let entry: [String] = native_list_get(vocab, i)")
+    L.append('        if str_eq(native_list_get(entry, 0), word) { return entry }')
+    L.append("        let i = i + 1")
+    L.append("    }")
+    L.append("    return native_list_empty()")
+    L.append("}")
+    with open(out_path, "w", encoding="utf-8") as fh:
+        fh.write("\n".join(L) + "\n")
+    return total, stats
+
+def emit(lang, out_path):
+    M = importlib.import_module(f"morphology_{lang}_full")
+    rows, stats = build_rows(lang, M)
+    return write_seed(lang, rows, stats, out_path)
+
+if __name__ == "__main__":
+    lang, out = sys.argv[1], sys.argv[2]
+    total, stats = emit(lang, out)
+    print(f"{lang}: wrote {out}  total={total} verbs={stats['verbs']} nouns={stats['nouns']} adjs={stats['adjs']}")