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.
Phase 3 piece 2. Ports multilingual.py: deterministic language detection
(en/es/pt/it) via stopword + diacritic scoring, localized fixed phrases (SACRED
per-language yes/no/decline/identity), PT/ES->EN retrieval term lexicon, and
EN->target predicate translation. No generative model.
Gate (multilingual_gate.el): 4/4 languages detected correctly; localized
declines + term/pred lexicons verified. Built bounded (elc rc=0 peak 25MB).
Worked through the documented el '+' mis-compile (two chained function-call Int
operands compile as string concat -> corrupt Int -> segfault on the accented
path); fixed by binding each score to an Int var and adding vars singly.
Simplifications (honest): diacritics scored by PRESENCE (str_contains) not
codepoint count (UTF-8 index safety); confidence scalar and the regex-based
parse_directive() from the reference not yet ported (directive parsing deferred
to the dialogue layer).
Phase 3 piece 1. Ports propositions.py off spaCy: the dependency-parser role is
now the el-native parser (parse_spec), and each memory sentence's meaning-spec
IS the triple (subject, predicate, object, modifiers, polarity, tense, source,
confidence). Sentence segmentation + repr parity with propositions.py. NEGATION
SACRED: polarity flows straight from the spec, never dropped/inverted.
Gate (propositions_gate.el): 4/4 SACRED polarity correct on extraction;
multi-sentence memory splits one triple per sentence in reading order with
negation preserved. Built bounded (elc rc=0 peak 24MB, cc rc=0).
Gap (honest): English regular-verb lemmatizer does not restore silent-e
(stores->stor); coreference/passive normalization from the reference not yet
ported (shallow pronoun subject kept as surface).
PIECE 1 — greenfield el-native parser (comprehend.el), spaCy-free:
- text -> meaning-spec via invertible English morphology (the realizer's own
irregular table run BACKWARD) + a deterministic clause grammar (subject/verb
boundary, roles, ditransitive iobj, PP adjuncts, subordination, coordination).
- NEGATION IS SACRED: explicit polarity field, always present, cross-lingual
lexeme set; standalone neg adverbs (never) captured separately.
- WSD by deterministic syntactic position over a fixed sense inventory
(flies->fly, like->comparison, saw->see); engram nearest-region is the
documented runtime upgrade hook (no external model).
Polarity threaded through the whole el contract (was previously dropped at the
boundary): realizer.el realize_lang honors polarity (English do-support /
adverbial / copular negation; generic preverbal negator for es/pt/ca/it/fr/de/ro)
and places iobj; elp.el build_form_from_json carries polarity/neg_word/iobj
across JSON; morphology.el gains 'fight'.
Acceptance (native el telephone test, comprehend_gate.el): on the 5 gate
sentences polarity PRESERVED 5/5 and EXTRACTED 5/5 through parse->realize->
re-parse; 4/5 byte-identical. Built bounded (elc rc=0, cc rc=0).
Implements a complete natural language generation stack in El:
- morphology.el: English pluralization, verb conjugation (40+ irregulars), determiner agreement
- vocabulary.el: inline seed lexicon (~100 entries: pronouns, nouns, verbs, adjectives, etc.)
- grammar.el: CFG rules (S/NP/VP/PP), slot-map driven tree generator, s-expression renderer
- realizer.el: semantic form -> English text with tense/aspect/agreement, do-support for questions
- nlg.el: JSON-driven public API tying all modules together
- tests/run.sh: acceptance corpus runner (6 tests, all passing)
will.anderson
Will Anderson