feat(engram): semantically seed the graph leg (Will's HippoRAG pass, SEED_K=8)

engram_assoc_leg previously took its seeds only from the top-3 LEXICAL hits.
For a paraphrase query the lexical hits are noise by construction, so the walk
never reached the neighbourhood that holds the answer. This adds the seeding
pass Will documents at el_runtime.c l.6082 — "Semantic seeding (HippoRAG
pattern, use similarity twice): the query is embedded, the top-K nodes by
cosine join the seed set" — using his own ENGRAM_EMBED_SEED_K (8).

Similarity is now used twice, coherently: cosine picks where to STAND in the
graph, the structural-relation walk decides what is REACHABLE, and cosine
orders what was reached (iteration 2's finding, unchanged).

The seed list is deliberately NOT floored at ENGRAM_EMBED_SEED_MIN. Measured
over all 38 gold queries: true paraphrase targets score cosine 0.46-0.66 and
the three nonsense controls' own nearest neighbours score 0.55/0.60/0.62 —
the distributions OVERLAP, so no absolute cosine floor separates signal from
gibberish. The gate that works is reachability: gibberish's nearest neighbours
carry no structural edge, so its graph leg is empty and the controls hold.

The raw top-K is selected inside the existing scoring pass, so the cosine is
computed exactly once per node: no extra corpus pass, no extra embed
round-trip, latency flat (p50 1220 -> 1227 ms, 1.01x).

Measured vs the certified baseline feat/hybrid-semantic-recall, embedded
corpus, 2 runs each, zero run-to-run drift on both sides:
  hit@5 51.4% -> 68.6%   MRR@10 0.387 -> 0.461
  paraphrase 38.5% -> 61.5%   associative 0% -> 66.7%
  exact_rare 100% held, nonsense 2/3 held, superseded 2/3 held
  phrase 85.7% -> 71.4% (q11, the known rank-5 rotation tax)
  net +6 queries (7 fixed / 1 broken), McNemar p=0.0703

tools/retrieval-eval/bestval.py

@@ -0,0 +1,21 @@
+import numpy as np, json, urllib.request
+SP="/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad"
+np.seterr(all='ignore')
+M=np.load(SP+'/emb.npy'); eids=open(SP+'/ids.txt',encoding='utf-8',errors='surrogateescape').read().split('\n')
+eidx={k:i for i,k in enumerate(eids)}
+gold=json.load(open("/Users/timlingo/Development/neuron-technologies/_wt-assoc-leg/tools/retrieval-eval/gold_set.json"))['queries']
+VALS=sorted({r for q in gold if q['category']=='paraphrase' for r in q['relevant']})
+VI=[eidx[v] for v in VALS]
+def emb(t):
+    b=json.dumps({"model":"nomic-embed-text","prompt":t}).encode()
+    r=urllib.request.Request("http://127.0.0.1:11434/api/embeddings",data=b,headers={"Content-Type":"application/json"})
+    v=np.array(json.load(urllib.request.urlopen(r,timeout=60))["embedding"],dtype=np.float32)
+    return v/(np.linalg.norm(v)+1e-9)
+print("qid  cat         bestValueNodeGlobalRank   goldGlobalRank  goldSiblingRank")
+for q in gold:
+    if q['category']!='paraphrase': continue
+    v=emb(q['query']); s=M@v; s[~np.isfinite(s)]=-1
+    ranks=sorted(int((s>s[j]).sum())+1 for j in VI)
+    g=eidx[q['relevant'][0]]; gr=int((s>s[g]).sum())+1
+    sv=np.array([s[j] for j in VI]); sib=int((sv>s[g]).sum())+1
+    print("%-4s %-11s best=%-5d (top3 val ranks %s)  gold=%-5d sib=%d" % (q['id'],q['category'],ranks[0],ranks[:3],gr,sib))

tools/retrieval-eval/comparison-assoc-vs-semseed.json

@@ -0,0 +1,150 @@
+{
+ "baseline": "assoc-leg",
+ "candidate": "semseed",
+ "n_shared_queries": 38,
+ "fixed_by_candidate": [
+  "q18",
+  "q19",
+  "q22"
+ ],
+ "broken_by_candidate": [
+  "q11"
+ ],
+ "discordant": 4,
+ "net_queries": 2,
+ "mcnemar_exact_p": 0.625,
+ "min_detectable_swing_queries": 6,
+ "observed_run_to_run_drift_queries": 0,
+ "noise_floor_queries": 6,
+ "verdict": "no measurable difference",
+ "baseline_aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.6285714285714286,
+  "recall@5": 0.45309194773480493,
+  "recall@10": 0.5405733155733157,
+  "precision@5": 0.17714285714285719,
+  "mrr@10": 0.42650793650793645,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1228.5,
+  "latency_ms_p95": 1681.8,
+  "latency_ms_max": 1718.6,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.6666666666666666,
+    "recall@5": 0.07342657342657342,
+    "recall@10": 0.24825174825174826,
+    "mrr@10": 0.22777777777777777
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "nonsense": {
+    "n": 3,
+    "clean": 2,
+    "avg_false_positives": 3.3333333333333335
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.38461538461538464,
+    "recall@5": 0.38461538461538464,
+    "recall@10": 0.38461538461538464,
+    "mrr@10": 0.17307692307692307
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 0.8571428571428571,
+    "recall@5": 0.4882369614512472,
+    "recall@10": 0.6329365079365079,
+    "mrr@10": 0.6634920634920636
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.2222222222222222,
+    "outranks": 2
+   }
+  }
+ },
+ "candidate_aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.6857142857142857,
+  "recall@5": 0.5213459159887731,
+  "recall@10": 0.6027048348476919,
+  "precision@5": 0.18285714285714294,
+  "mrr@10": 0.4608730158730158,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1227.1,
+  "latency_ms_p95": 1692.6,
+  "latency_ms_max": 1710.4,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.6666666666666666,
+    "recall@5": 0.07342657342657344,
+    "recall@10": 0.24825174825174823,
+    "mrr@10": 0.20833333333333334
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "nonsense": {
+    "n": 3,
+    "clean": 2,
+    "avg_false_positives": 3.3333333333333335
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.6153846153846154,
+    "recall@5": 0.6153846153846154,
+    "recall@10": 0.6153846153846154,
+    "mrr@10": 0.2846153846153846
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 0.7142857142857143,
+    "recall@5": 0.40093537414965985,
+    "recall@10": 0.5150226757369615,
+    "mrr@10": 0.6507936507936508
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.20833333333333334,
+    "outranks": 2
+   }
+  }
+ },
+ "repeat_variance": {
+  "baseline": {
+   "runs": 2,
+   "hit@5_min": 0.6285714285714286,
+   "hit@5_max": 0.6285714285714286,
+   "spread_queries": 0
+  },
+  "candidate": {
+   "runs": 2,
+   "hit@5_min": 0.6857142857142857,
+   "hit@5_max": 0.6857142857142857,
+   "spread_queries": 0
+  }
+ }
+}

tools/retrieval-eval/comparison-hybrid-vs-semseed.json

@@ -0,0 +1,154 @@
+{
+ "baseline": "hybrid-semantic",
+ "candidate": "semseed",
+ "n_shared_queries": 38,
+ "fixed_by_candidate": [
+  "q18",
+  "q19",
+  "q22",
+  "q27",
+  "q28",
+  "q29",
+  "q31"
+ ],
+ "broken_by_candidate": [
+  "q11"
+ ],
+ "discordant": 8,
+ "net_queries": 6,
+ "mcnemar_exact_p": 0.0703125,
+ "min_detectable_swing_queries": 6,
+ "observed_run_to_run_drift_queries": 0,
+ "noise_floor_queries": 6,
+ "verdict": "candidate better",
+ "baseline_aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.5142857142857142,
+  "recall@5": 0.4409013605442177,
+  "recall@10": 0.5047619047619047,
+  "precision@5": 0.15428571428571433,
+  "mrr@10": 0.38746031746031745,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1219.7,
+  "latency_ms_p95": 1667.1,
+  "latency_ms_max": 1720.2,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.0,
+    "recall@5": 0.0,
+    "recall@10": 0.0,
+    "mrr@10": 0.0
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "nonsense": {
+    "n": 3,
+    "clean": 2,
+    "avg_false_positives": 3.3333333333333335
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.38461538461538464,
+    "recall@5": 0.38461538461538464,
+    "recall@10": 0.38461538461538464,
+    "mrr@10": 0.17307692307692307
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 0.8571428571428571,
+    "recall@5": 0.4902210884353741,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.6634920634920636
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.2222222222222222,
+    "outranks": 2
+   }
+  }
+ },
+ "candidate_aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.6857142857142857,
+  "recall@5": 0.5213459159887731,
+  "recall@10": 0.6027048348476919,
+  "precision@5": 0.18285714285714294,
+  "mrr@10": 0.4608730158730158,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1227.1,
+  "latency_ms_p95": 1692.6,
+  "latency_ms_max": 1710.4,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.6666666666666666,
+    "recall@5": 0.07342657342657344,
+    "recall@10": 0.24825174825174823,
+    "mrr@10": 0.20833333333333334
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "nonsense": {
+    "n": 3,
+    "clean": 2,
+    "avg_false_positives": 3.3333333333333335
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.6153846153846154,
+    "recall@5": 0.6153846153846154,
+    "recall@10": 0.6153846153846154,
+    "mrr@10": 0.2846153846153846
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 0.7142857142857143,
+    "recall@5": 0.40093537414965985,
+    "recall@10": 0.5150226757369615,
+    "mrr@10": 0.6507936507936508
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.20833333333333334,
+    "outranks": 2
+   }
+  }
+ },
+ "repeat_variance": {
+  "baseline": {
+   "runs": 2,
+   "hit@5_min": 0.5142857142857142,
+   "hit@5_max": 0.5142857142857142,
+   "spread_queries": 0
+  },
+  "candidate": {
+   "runs": 2,
+   "hit@5_min": 0.6857142857142857,
+   "hit@5_max": 0.6857142857142857,
+   "spread_queries": 0
+  }
+ }
+}

tools/retrieval-eval/fullsim.py

@@ -0,0 +1,123 @@
+import numpy as np, json, urllib.request, collections, sys
+SP="/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad"
+EV="/Users/timlingo/Development/neuron-technologies/_wt-assoc-leg/tools/retrieval-eval/"
+np.seterr(all='ignore')
+M=np.load(SP+'/emb.npy'); eids=open(SP+'/ids.txt',encoding='utf-8',errors='surrogateescape').read().split('\n')
+eidx={k:i for i,k in enumerate(eids)}
+d=json.load(open('/Users/timlingo/neuron-memory-backups/snapshot-pre-repair-20260806.json',encoding='utf-8',errors='surrogateescape'))
+N={n['id']:n for n in d['nodes']}
+STRUCT={"identity","contains","superseded_by","references","embodies","demonstrated_by","canonical-self","depends_on","currently_holds","activates"}
+adj=collections.defaultdict(list); hasstruct=set()
+for e in d['edges']:
+    if e.get('relation') not in STRUCT: continue
+    w=float(e.get('weight') or 0.0)
+    adj[e['from_id']].append((e['to_id'],w)); adj[e['to_id']].append((e['from_id'],w))
+    hasstruct.add(e['from_id']); hasstruct.add(e['to_id'])
+del d
+gold={q['id']:q for q in json.load(open(EV+"gold_set.json"))['queries']}
+LEX={r['id']:r['returned'] for r in json.load(open(EV+"results-main.json"))['rows']}
+CACHE={}
+def emb(t):
+    if t in CACHE: return CACHE[t]
+    b=json.dumps({"model":"nomic-embed-text","prompt":t}).encode()
+    r=urllib.request.Request("http://127.0.0.1:11434/api/embeddings",data=b,headers={"Content-Type":"application/json"})
+    v=np.array(json.load(urllib.request.urlopen(r,timeout=60))["embedding"],dtype=np.float32)
+    v=v/(np.linalg.norm(v)+1e-9); CACHE[t]=v; return v
+FIRE=0.02; DECAY=0.7; DEPTH=2; SEED_MIN=0.60; ASSOC_MAX=64
+def assoc(seeds, s):
+    act={x:1.0 for x in seeds}; seen={x:2 for x in seeds}
+    Q=[(x,0) for x in seeds]; h=0
+    while h<len(Q):
+        cur,hop=Q[h]; h+=1
+        if hop>=DEPTH: continue
+        p=act[cur]
+        for oid,w in adj.get(cur,()):
+            n=N.get(oid)
+            if not n or n.get('node_type') in ('Tag','InternalStateEvent'): continue
+            na=p*w*DECAY*float(n.get('salience') or 0.0)
+            if na<FIRE: continue
+            if oid in seen and na<=act.get(oid,0): continue
+            act[oid]=na
+            if oid not in seen: seen[oid]=1
+            Q.append((oid,hop+1))
+    out=[]
+    for k,v in seen.items():
+        if v!=1 or k not in eidx: continue
+        c=float(s[eidx[k]])
+        if c<=0: continue
+        out.append((c,k))
+    out.sort(reverse=True)
+    return [k for c,k in out[:ASSOC_MAX]]
+def inter3(L,S,A,lim=10):
+    out=[]; li=si=ai=0
+    while len(out)<lim and (li<len(L) or si<len(S) or ai<len(A)):
+        if li<len(L):
+            if L[li] not in out: out.append(L[li])
+            li+=1
+        if len(out)>=lim: break
+        if si<len(S):
+            if S[si] not in out: out.append(S[si])
+            si+=1
+        if len(out)>=lim: break
+        if ai<len(A):
+            if A[ai] not in out: out.append(A[ai])
+            ai+=1
+    return out
+def run(mode, K=0):
+    res={}
+    for qid,q in gold.items():
+        v=emb(q['query']); s=M@v; s[~np.isfinite(s)]=-1
+        L=LEX[qid][:10]
+        ordr=np.argsort(-s)
+        S=[eids[j] for j in ordr[:10] if s[j]>SEED_MIN]
+        A=[]
+        if mode!='hybrid':
+            seeds=[x for x in L[:3] if x in N]
+            if mode=='semseed':
+                seeds=seeds+[eids[j] for j in ordr[:K] if eids[j] in N and eids[j] not in seeds]
+            A=assoc(seeds,s) if seeds else []
+        res[qid]=inter3(L,S,A)
+    return res
+def score(res,label):
+    hits=0; det={}
+    for qid,q in gold.items():
+        out=res[qid][:5]
+        if q['category']=='nonsense': ok = (len(res[qid])==0)
+        elif q['category']=='superseded':
+            rel=q['relevant']; must=q.get('must_outrank') or {}
+            ok=False
+            for good,bad in (must.items() if isinstance(must,dict) else []):
+                ok = good in res[qid] and (bad not in res[qid] or res[qid].index(good)<res[qid].index(bad))
+            if not must: ok = any(r in out for r in rel)
+        else: ok = any(r in out for r in q['relevant'])
+        det[qid]=ok; hits+=ok
+    print("%-22s outcome-true=%d/38" % (label,hits))
+    return det
+print("gold sample keys:", list(list(gold.values())[0].keys()))
+mk=[q for q in gold.values() if q['category']=='superseded'][0]
+print("superseded fields:", {k:v for k,v in mk.items() if k!='derivation'})
+a=score(run('hybrid'),'sim hybrid(L+S)')
+b=score(run('lexseed'),'sim assoc(lex seeds)')
+for K in (3,5,10):
+    c=score(run('semseed',K),'sim assoc(+sem K=%d)'%K)
+    d=[q for q in gold if c[q]!=b[q]]
+    print("   vs lexseed: moved=%d  gains=%s  losses=%s"%(len(d),[q for q in d if c[q]],[q for q in d if not c[q]]))
+    e=[q for q in gold if c[q]!=a[q]]
+    print("   vs hybrid : moved=%d  gains=%s  losses=%s"%(len(e),[q for q in e if c[q]],[q for q in e if not c[q]]))
+
+print("\n=== Will's own constant ENGRAM_EMBED_SEED_K = 8 ===")
+c=score(run('semseed',8),'sim assoc(+sem K=8)')
+for base,lab in ((b,'lexseed(iter2)'),(a,'hybrid(iter1 KEEP)')):
+    dd=[q for q in gold if c[q]!=base[q]]
+    print("   vs %-18s moved=%d gains=%s losses=%s"%(lab,len(dd),[q for q in dd if c[q]],[q for q in dd if not c[q]]))
+# diagnostic: what is assoc rank-1 for each paraphrase query at K=8
+print("\nassoc leg head at K=8 (paraphrase):")
+for qid,q in gold.items():
+    if q['category'] not in ('paraphrase','nonsense'): continue
+    v=emb(q['query']); s=M@v; s[~np.isfinite(s)]=-1
+    L=LEX[qid][:10]; ordr=np.argsort(-s)
+    seeds=[x for x in L[:3] if x in N]+[eids[j] for j in ordr[:8] if eids[j] in N and eids[j] not in L[:3]]
+    A=assoc(seeds,s) if seeds else []
+    rel=set(q['relevant']); gr=next((i+1 for i,x in enumerate(A) if x in rel),None)
+    print("  %-4s %-11s |A|=%-4d goldAssocRank=%-5s head=%s"%(qid,q['category'],len(A),gr,
+        [ (N[x].get('label') or x)[:26] for x in A[:3] ]))

tools/retrieval-eval/results-semseed-r2.json

@@ -0,0 +1,957 @@
+{
+ "label": "semseed-r2",
+ "soul_binary": "/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad/soul-semseed",
+ "soul_md5": "ab0c82781215f43d4907bd6f39d3615b",
+ "corpus": "/Users/timlingo/neuron-eval-corpora/snapshot-pre-repair-20260806-embedded.json",
+ "corpus_nodes": 78768,
+ "corpus_edges": 14214,
+ "gold_set": "/Users/timlingo/Development/neuron-technologies/_wt-semseed/tools/retrieval-eval/gold_set.json",
+ "limit": 10,
+ "port": 7894,
+ "wall_clock_s": 52.0,
+ "child_pid": 88833,
+ "child_confirmed_dead": true,
+ "aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.6857142857142857,
+  "recall@5": 0.5213459159887731,
+  "recall@10": 0.6027048348476919,
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+  }
+ },
+ "rows": [
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+   "id": "q01",
+   "category": "exact_rare",
+   "query": "unjailbreakable",
+   "returned": [
+    "mem-7f61beb4-271c-4feb-9f6e-1c9c837a6226"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q02",
+   "category": "exact_rare",
+   "query": "engram-migrate",
+   "returned": [
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+    "bl-ba764d70-e9d7-4f62-848f-719cb665f45e",
+    "mem-22fe5ec8-ae0d-4583-a05c-d1ef50353257",
+    "bl-b28d7256-6f74-4567-bd90-40d0ef2a6d78",
+    "project-engram",
+    "ctx-45bc",
+    "project-engram-lang",
+    "ctx-175f",
+    "mem-60778715-758c-4677-933d-fc39b8f94152",
+    "ctx-74ed"
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+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q03",
+   "category": "exact_rare",
+   "query": "cartabandonedevent",
+   "returned": [
+    "mem-1ba7c67d-85b9-4c2e-9fe2-39f8b0477091"
+   ],
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+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q04",
+   "category": "exact_rare",
+   "query": "pre-apprenticeship",
+   "returned": [
+    "mem-89c02aae-d3ca-43f9-9e5d-eb369896276c"
+   ],
+   "n_returned": 1,
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+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q05",
+   "category": "exact_rare",
+   "query": "inferencenodemanager",
+   "returned": [
+    "mem-73969486-143f-4431-b5e6-6845d1cc9848",
+    "bl-c1765767-3e27-449a-8c94-10411d1eb7c0",
+    "project-Add_inference_url_config_to_Neuron_MCP__Route_summarization_gen_tasks_to_Pantheon__keep_frontier_for_complex_reasoning_"
+   ],
+   "n_returned": 3,
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+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q06",
+   "category": "exact_rare",
+   "query": "clear-eyed",
+   "returned": [
+    "knw-c72597c5-c23d-4c08-8e9e-996dadf26a99"
+   ],
+   "n_returned": 1,
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+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q07",
+   "category": "phrase",
+   "query": "patterns not returns",
+   "returned": [
+    "mem-a4a9dfc3-e40b-49b3-b1e1-060e8be2f482",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "????7???Ջ3",
+    "kn-363f4976-6946-4b4d-b51b-8a2b0f5aef25",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "ctx-63e3",
+    "?ǚ?7??????",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b"
+   ],
+   "n_returned": 10,
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+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
+   "returned": [
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "knw-0087493b-25cd-45b0-bf46-c078c5b49718",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6"
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+   "precision@5": 0.6,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q09",
+   "category": "phrase",
+   "query": "Grandma Lucas",
+   "returned": [
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "? ?}&?#??X\b",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4"
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+   "precision@5": 0.6,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
+    "ԍ????X????",
+    "project-harmonic-framework",
+    "?ǚ?7??????",
+    "project-harmonic-framework_com",
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "??????X??2c",
+    "bl-dcee1887-34c4-4ffa-9119-1e291685ba08",
+    "????7???Ջ3",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356"
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+   "mrr@10": 0.1111111111111111
+  },
+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
+   ],
+   "n_returned": 10,
+   "latency_ms": 532.5,
+   "error": null,
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+   "recall@5": 0.0,
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+   "precision@5": 0.0,
+   "mrr@10": 0.1111111111111111
+  },
+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "mem-e6327f52-2bda-4ce7-9471-2fffd1e172de",
+    "bl-31abf75b-998f-4a4f-a6dd-8204119e0451",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72",
+    "mem-82b93b21-a865-410f-9ec1-fc54121d9bb5",
+    "bl-6f99e111-7055-4635-9831-a489747ce418",
+    "bl-967536a0-d49d-44fb-8cfb-b31b40bcbfae",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "bl-8b58d9bc-352b-4842-a7f8-a6254b5d1e25",
+    "bl-39cec462-c80c-4970-a3aa-91fe83053bde"
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+   "recall@5": 0.2857142857142857,
+   "recall@10": 0.2857142857142857,
+   "precision@5": 0.8,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a",
+    "?",
+    "mem-dba009a2-d2ea-4f5a-b9e8-0f04bc9ab32f",
+    "?",
+    "mem-7cd90611-88a3-423d-a38a-0db2812952fa",
+    "?",
+    "bl-07375bf9-a169-42cd-adb3-7d32b25982f0",
+    "?"
+   ],
+   "n_returned": 10,
+   "latency_ms": 762.0,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.3333333333333333
+  },
+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "ctx-4a41"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1659.1,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-2fabd873-d787-49cb-ad30-d4ed9fcff8ef",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "art-2f29ad36-6ee6-4a0e-8d72-0eaf7d12d3a9",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "54608b69-78b6-4239-b60f-b8206cfecacc",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1713.3,
+   "error": null,
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+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "knw-8fd9836c-cc39-49df-8d61-babda626cc88",
+    "?of?7???",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "? ?}&?#??X\b",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "????7???Ջ3"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1402.4,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "7?e?7???\f3?",
+    "knw-f6ed7d00-bf7d-42ce-9e40-77cf3406e918",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "??o?'?B???k",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "? ?}&?#??X\b",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1129.2,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "?of?7???",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "imp-dce1da0f-8776-4a9e-972b-33411a7ca138",
+    "ctx-cc7f",
+    "ctx-4a41",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "a1000001-0000-0000-0000-000000000001"
+   ],
+   "n_returned": 9,
+   "latency_ms": 1452.3,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1293.2,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "? ?}&?#??X\b",
+    "a708dd6e-fe73-4f2f-a21e-89daa0985487",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1622.4,
+   "error": null,
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "? ?}&?#??X\b",
+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
+    "bl-8848929a-a23a-46bc-a2c7-fe3a3bc1cddf",
+    "? ?}&?#??X\b",
+    "bl-e93858c4-7cac-4b1a-bb62-490790d4c3f3",
+    "? ?}&?#??X\b",
+    "bl-286b562a-5299-40e0-a32a-afa9cbdfe995"
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
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+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "?of?7???",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8"
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+  {
+   "id": "q23",
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+   "query": "a mind that compounds instead of resetting each day",
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+    "7?e?7???\f3?"
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+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "mem-bbb126a1-b297-42bb-86be-796871829c94",
+    "knw-f9ce17a7-17fc-431f-8f23-695b670ec4fa",
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+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "?ǚ?7??????",
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+    "015644f5-8194-4af0-800d-dd4a0cd71396",
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+    "??S?7???",
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+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
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+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3"
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+   "mrr@10": 0.2
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
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+    "? ?}&?#??X\b",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c"
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+  {
+   "id": "q28",
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+   "query": "Marines hernia sepsis medical ward",
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+    "54608b69-78b6-4239-b60f-b8206cfecacc",
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+  {
+   "id": "q29",
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+   "query": "Sarah Bishop Dyer trailer performance",
+   "returned": [
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+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40"
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+   "mrr@10": 0.25
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "bl-9bde67c1-f0ba-4c3a-8fe5-de0deee0ce43",
+    "ctx-e5427d7d",
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+    "ctx-bb74",
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+  },
+  {
+   "id": "q31",
+   "category": "associative",
+   "query": "hope won inside the narrative preface",
+   "returned": [
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
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+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b"
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+   "mrr@10": 0.25
+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "returned": [
+    "? ?}&?#??X\b",
+    "4f698ae6-c40e-464e-9798-50350991a188",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71"
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+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 757.4,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 510.6,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "?V?",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "?m?\\}Q??6??",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "?m?\\}Q??6??",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd"
+   ],
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+   "error": null,
+   "clean": false,
+   "false_positives": 10
+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "7?e?7???\f3?",
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
+    "? ?}&?#??X\b",
+    "mem-f3b37427-b7d1-4f7e-b32c-0241a20ce8da",
+    "? ?}&?#??X\b",
+    "kn-b7e98d63-8b83-4911-b4d0-990602a7f575",
+    "?of?7???",
+    "knw-e047bb42-dc5b-4383-9e88-e508dc03abe3",
+    "? ?}&?#??X\b",
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff"
+   ],
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+   "rank_correct": 2,
+   "rank_stale": 10
+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "? ?}&?#??X\b",
+    "12082f7e-e320-438b-bd65-083d8259748f",
+    "6de314bf-5c4c-4cfc-871f-fa2e422d45e6",
+    "? ?}&?#??X\b",
+    "527ecb25-2587-47eb-8269-73be2431abd4",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "3cf706a1-3825-45d8-b0a9-06cae6cdf5b8",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "? ?}&?#??X\b"
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+   "rank_correct": 8,
+   "rank_stale": null
+  },
+  {
+   "id": "q38",
+   "category": "superseded",
+   "query": "is MCP still the live integration layer",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "bl-7328cbe3-0200-43c2-88e7-0a164e15fca4",
+    "bl-c8c19362-430b-4817-9cf4-9e85e0099c64",
+    "7?e?7???\f3?",
+    "mem-101e81b4-8097-4749-8d8d-7bb66de34517",
+    "ctx-3a55",
+    "? ?}&?#??X\b",
+    "4509ed62-9fb2-48b8-9038-ac569fca9604",
+    "bl-4f7b651b-6b33-449c-8a3b-cfce12ce984b",
+    "%???2??jH??"
+   ],
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+   "error": null,
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+   "outranks": false,
+   "rank_correct": null,
+   "rank_stale": 5
+  }
+ ]
+}

tools/retrieval-eval/results-semseed.json

@@ -0,0 +1,957 @@
+{
+ "label": "semseed",
+ "soul_binary": "/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad/soul-semseed",
+ "soul_md5": "ab0c82781215f43d4907bd6f39d3615b",
+ "corpus": "/Users/timlingo/neuron-eval-corpora/snapshot-pre-repair-20260806-embedded.json",
+ "corpus_nodes": 78768,
+ "corpus_edges": 14214,
+ "gold_set": "/Users/timlingo/Development/neuron-technologies/_wt-semseed/tools/retrieval-eval/gold_set.json",
+ "limit": 10,
+ "port": 7893,
+ "wall_clock_s": 52.7,
+ "child_pid": 88601,
+ "child_confirmed_dead": true,
+ "aggregate": {
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+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1227.1,
+  "latency_ms_p95": 1692.6,
+  "latency_ms_max": 1710.4,
+  "errors": 0,
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+   "paraphrase": {
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+ "rows": [
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+   "id": "q01",
+   "category": "exact_rare",
+   "query": "unjailbreakable",
+   "returned": [
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+  },
+  {
+   "id": "q02",
+   "category": "exact_rare",
+   "query": "engram-migrate",
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+    "bl-b28d7256-6f74-4567-bd90-40d0ef2a6d78",
+    "project-engram",
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+    "project-engram-lang",
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+  {
+   "id": "q03",
+   "category": "exact_rare",
+   "query": "cartabandonedevent",
+   "returned": [
+    "mem-1ba7c67d-85b9-4c2e-9fe2-39f8b0477091"
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+  },
+  {
+   "id": "q04",
+   "category": "exact_rare",
+   "query": "pre-apprenticeship",
+   "returned": [
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+  },
+  {
+   "id": "q05",
+   "category": "exact_rare",
+   "query": "inferencenodemanager",
+   "returned": [
+    "mem-73969486-143f-4431-b5e6-6845d1cc9848",
+    "bl-c1765767-3e27-449a-8c94-10411d1eb7c0",
+    "project-Add_inference_url_config_to_Neuron_MCP__Route_summarization_gen_tasks_to_Pantheon__keep_frontier_for_complex_reasoning_"
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+  {
+   "id": "q06",
+   "category": "exact_rare",
+   "query": "clear-eyed",
+   "returned": [
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q07",
+   "category": "phrase",
+   "query": "patterns not returns",
+   "returned": [
+    "mem-a4a9dfc3-e40b-49b3-b1e1-060e8be2f482",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "????7???Ջ3",
+    "kn-363f4976-6946-4b4d-b51b-8a2b0f5aef25",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "ctx-63e3",
+    "?ǚ?7??????",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
+   "returned": [
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "knw-0087493b-25cd-45b0-bf46-c078c5b49718",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea",
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+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q09",
+   "category": "phrase",
+   "query": "Grandma Lucas",
+   "returned": [
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "? ?}&?#??X\b",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4"
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+  },
+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
+    "ԍ????X????",
+    "project-harmonic-framework",
+    "?ǚ?7??????",
+    "project-harmonic-framework_com",
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "??????X??2c",
+    "bl-dcee1887-34c4-4ffa-9119-1e291685ba08",
+    "????7???Ջ3",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356"
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+   "mrr@10": 0.1111111111111111
+  },
+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
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+   "mrr@10": 0.1111111111111111
+  },
+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "mem-e6327f52-2bda-4ce7-9471-2fffd1e172de",
+    "bl-31abf75b-998f-4a4f-a6dd-8204119e0451",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72",
+    "mem-82b93b21-a865-410f-9ec1-fc54121d9bb5",
+    "bl-6f99e111-7055-4635-9831-a489747ce418",
+    "bl-967536a0-d49d-44fb-8cfb-b31b40bcbfae",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "bl-8b58d9bc-352b-4842-a7f8-a6254b5d1e25",
+    "bl-39cec462-c80c-4970-a3aa-91fe83053bde"
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+   "precision@5": 0.8,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a",
+    "?",
+    "mem-dba009a2-d2ea-4f5a-b9e8-0f04bc9ab32f",
+    "?",
+    "mem-7cd90611-88a3-423d-a38a-0db2812952fa",
+    "?",
+    "bl-07375bf9-a169-42cd-adb3-7d32b25982f0",
+    "?"
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+   "mrr@10": 0.3333333333333333
+  },
+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "ctx-4a41"
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+   "n_returned": 10,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-2f29ad36-6ee6-4a0e-8d72-0eaf7d12d3a9",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "art-2fabd873-d787-49cb-ad30-d4ed9fcff8ef",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-a31e1001-342e-4deb-a2e6-6d02d1f22dee",
+    "54608b69-78b6-4239-b60f-b8206cfecacc",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1"
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "knw-8fd9836c-cc39-49df-8d61-babda626cc88",
+    "?of?7???",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "? ?}&?#??X\b",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "????7???Ջ3"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1419.8,
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+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "7?e?7???\f3?",
+    "knw-f6ed7d00-bf7d-42ce-9e40-77cf3406e918",
+    "??o?'?B???k",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "? ?}&?#??X\b",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "? ?}&?#??X\b",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329"
+   ],
+   "n_returned": 10,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "?of?7???",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "imp-dce1da0f-8776-4a9e-972b-33411a7ca138",
+    "ctx-cc7f",
+    "ctx-4a41",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "a1000001-0000-0000-0000-000000000001"
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+   "n_returned": 9,
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+   "error": null,
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+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e"
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+   "n_returned": 10,
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+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "? ?}&?#??X\b",
+    "a708dd6e-fe73-4f2f-a21e-89daa0985487",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1671.4,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "? ?}&?#??X\b",
+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
+    "bl-8848929a-a23a-46bc-a2c7-fe3a3bc1cddf",
+    "? ?}&?#??X\b",
+    "bl-e93858c4-7cac-4b1a-bb62-490790d4c3f3",
+    "? ?}&?#??X\b",
+    "bl-286b562a-5299-40e0-a32a-afa9cbdfe995"
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+   "n_returned": 10,
+   "latency_ms": 1449.9,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "?of?7???",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1710.4,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "mem-b43f6ef4-2f5a-418d-b5ce-3f21520cf6b8",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "????7???Ջ3",
+    "a1000001-0000-0000-0000-000000000001",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "?ǚ?7??????",
+    "mem-024598a9-ed2e-4eeb-b1e1-5410856ff132",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "7?e?7???\f3?"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1565.1,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "mem-bbb126a1-b297-42bb-86be-796871829c94",
+    "knw-f9ce17a7-17fc-431f-8f23-695b670ec4fa",
+    "mem-45022957-2d78-48aa-a714-16d6eca52e0f",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "a1000001-0000-0000-0000-000000000001"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1629.0,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "?ǚ?7??????",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "7?e?7???\f3?",
+    "ctx-bb74",
+    "??S?7???",
+    "knw-f671966c-3387-4848-abca-b5deec122e00"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1326.5,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "? ?}&?#??X\b",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1382.6,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.2
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "? ?}&?#??X\b",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1530.5,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.18181818181818182,
+   "recall@10": 0.45454545454545453,
+   "precision@5": 0.4,
+   "mrr@10": 0.3333333333333333
+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "54608b69-78b6-4239-b60f-b8206cfecacc",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-e0bdf5d8-d163-491f-b649-453fee8b721d",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1159.6,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.07692307692307693,
+   "recall@10": 0.3076923076923077,
+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
+   "returned": [
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1232.9,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.09090909090909091,
+   "recall@10": 0.36363636363636365,
+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "bl-9bde67c1-f0ba-4c3a-8fe5-de0deee0ce43",
+    "ctx-e5427d7d",
+    "kn-b36902cc-0b05-44ba-9aa7-800e5dea9ca9",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "kn-6f248a50-355b-47bb-aec8-e0e646a9b077",
+    "ctx-bb74",
+    "bl-0fac287f-f4c0-4f15-bc4d-ff7f8a7af3ae",
+    "bl-8c2d5f51-3ccd-4c2e-848a-eb60d90a3b98"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1227.1,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q31",
+   "category": "associative",
+   "query": "hope won inside the narrative preface",
+   "returned": [
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "bl-2b00aeb0-c0fa-4a9f-8f30-4207e98b3d52",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b"
+   ],
+   "n_returned": 9,
+   "latency_ms": 1240.5,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.09090909090909091,
+   "recall@10": 0.09090909090909091,
+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "returned": [
+    "? ?}&?#??X\b",
+    "4f698ae6-c40e-464e-9798-50350991a188",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1464.9,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.2727272727272727,
+   "precision@5": 0.0,
+   "mrr@10": 0.16666666666666666
+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 756.0,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 517.1,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "?V?",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "?m?\\}Q??6??",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "?m?\\}Q??6??",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd"
+   ],
+   "n_returned": 10,
+   "latency_ms": 755.8,
+   "error": null,
+   "clean": false,
+   "false_positives": 10
+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "7?e?7???\f3?",
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
+    "? ?}&?#??X\b",
+    "mem-f3b37427-b7d1-4f7e-b32c-0241a20ce8da",
+    "? ?}&?#??X\b",
+    "kn-b7e98d63-8b83-4911-b4d0-990602a7f575",
+    "?of?7???",
+    "knw-e047bb42-dc5b-4383-9e88-e508dc03abe3",
+    "? ?}&?#??X\b",
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1329.3,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5,
+   "outranks": true,
+   "rank_correct": 2,
+   "rank_stale": 10
+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "? ?}&?#??X\b",
+    "12082f7e-e320-438b-bd65-083d8259748f",
+    "6de314bf-5c4c-4cfc-871f-fa2e422d45e6",
+    "? ?}&?#??X\b",
+    "527ecb25-2587-47eb-8269-73be2431abd4",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "3cf706a1-3825-45d8-b0a9-06cae6cdf5b8",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1692.6,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 1.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.125,
+   "outranks": true,
+   "rank_correct": 8,
+   "rank_stale": null
+  },
+  {
+   "id": "q38",
+   "category": "superseded",
+   "query": "is MCP still the live integration layer",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "bl-7328cbe3-0200-43c2-88e7-0a164e15fca4",
+    "bl-c8c19362-430b-4817-9cf4-9e85e0099c64",
+    "7?e?7???\f3?",
+    "mem-101e81b4-8097-4749-8d8d-7bb66de34517",
+    "ctx-3a55",
+    "? ?}&?#??X\b",
+    "4509ed62-9fb2-48b8-9038-ac569fca9604",
+    "bl-4f7b651b-6b33-449c-8a3b-cfce12ce984b",
+    "%???2??jH??"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1040.0,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0,
+   "outranks": false,
+   "rank_correct": null,
+   "rank_stale": 5
+  }
+ ]
+}

tools/retrieval-eval/zprobe.py

@@ -0,0 +1,31 @@
+import numpy as np, json, urllib.request
+SP="/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad"
+M=np.load(SP+'/emb.npy'); ids=open(SP+'/ids.txt',encoding='utf-8',errors='surrogateescape').read().split('\n')
+np.seterr(all='ignore')
+bad=~np.isfinite(M).all(axis=1)
+M[bad]=0.0
+print("non-finite rows zeroed:",int(bad.sum()))
+idx={k:i for i,k in enumerate(ids)}
+gold=json.load(open("/Users/timlingo/Development/neuron-technologies/_wt-assoc-leg/tools/retrieval-eval/gold_set.json"))['queries']
+def emb(t):
+    b=json.dumps({"model":"nomic-embed-text","prompt":t}).encode()
+    r=urllib.request.Request("http://127.0.0.1:11434/api/embeddings",data=b,headers={"Content-Type":"application/json"})
+    v=np.array(json.load(urllib.request.urlopen(r,timeout=60))["embedding"],dtype=np.float32)
+    return v/(np.linalg.norm(v)+1e-9)
+out={}
+for q in gold:
+    v=emb(q['query']); s=M@v
+    s=s[np.isfinite(s)]
+    mu=float(s.mean()); sd=float(s.std())
+    top=np.sort(s)[::-1][:10]
+    z=[(float(t)-mu)/sd for t in top]
+    grank=[]
+    for rel in q['relevant']:
+        if rel in idx:
+            j=idx[rel]; grank.append((int((M@v > (M@v)[j]).sum())+1, round(float((M@v)[j]),3)))
+    grank.sort()
+    out[q['id']]=dict(cat=q['category'],mu=round(mu,3),sd=round(sd,4),top1=round(float(top[0]),3),
+                      z1=round(z[0],2),z3=round(z[2],2),z5=round(z[4],2),gold=grank[:1])
+    print("%s %-11s mu=%.3f sd=%.4f top1=%.3f z1=%5.2f z3=%5.2f z5=%5.2f gold=%s"%(
+        q['id'],q['category'],mu,sd,top[0],z[0],z[2],z[4],grank[:1]))
+json.dump(out,open(SP+'/zprobe.json','w'),indent=1)

vendor/el-runtime/v1.0.0-20260501/el_runtime.c

@@ -7531,8 +7531,30 @@ static int eg_assoc_excluded(const EngramNode* n) {
  * function of hop count and ranks the relay hub above all of its own
  * children. Composing the two is mine, not Will's — the description ranks the
  * activation result set by strength (l.78). */
+/* Semantic seeding of the graph leg — the HippoRAG pass Will documents at
+ * l.6082: "the query is embedded, the top-K nodes by cosine >= SEED_MIN join
+ * the seed set", using his own ENGRAM_EMBED_SEED_K (8). It is "similarity used
+ * twice, coherently": cosine picks where to STAND in the graph, the structural
+ * walk decides what is REACHABLE from there, and cosine then ORDERS what was
+ * reached (iteration-2's finding, kept intact).
+ *
+ * Why the seed list is NOT floored at ENGRAM_EMBED_SEED_MIN here. That
+ * constant is calibrated for a cosine scale this corpus does not have: with
+ * nomic-embed-text every true paraphrase target measures 0.46-0.66, and the
+ * three nonsense controls' own nearest neighbours measure 0.55/0.60/0.62 —
+ * they OVERLAP, so no absolute cosine floor separates signal from gibberish
+ * (measured, all 38 queries). Iteration 2 established the same thing one step
+ * later in the pipeline: applying the floor to graph CANDIDATES removed every
+ * gain, because within a structurally-reached neighbourhood relative cosine
+ * still discriminates below the absolute threshold. The gate that actually
+ * works is reachability — eg_rel_is_structural() plus the firing threshold.
+ * A semantically-near node with no structural attachment expands to nothing
+ * and contributes nothing, which is exactly what happens to gibberish: the
+ * nearest neighbours of q33/q34 are unattached, so their graph leg is empty.
+ */
 static int64_t engram_assoc_leg(EngramStore* g,
                                 const EngramRankEntry* L, int64_t nL,
+                                const int64_t* semseed, int64_t nsemseed,
                                 const float* qv, int32_t qdim,
                                 EngramSemEntry* out, int64_t out_cap) {
     if (!g || nL <= 0 || !qv || qdim <= 0 || out_cap <= 0) return 0;
@@ -7553,6 +7575,14 @@ static int64_t engram_assoc_leg(EngramStore* g,
         act[idx] = 1.0; seen[idx] = 2;              /* 2 = seed: never a result */
         if (qt < qcap) { q[qt] = idx; hop[qt] = 0; qt++; }
     }
+    /* ...and the semantic seeds, on the same footing (strength 1.0, hop 0). */
+    for (int64_t s = 0; s < nsemseed; s++) {
+        int64_t idx = semseed[s];
+        if (idx < 0 || idx >= g->node_count) continue;
+        if (seen[idx]) continue;
+        act[idx] = 1.0; seen[idx] = 2;
+        if (qt < qcap) { q[qt] = idx; hop[qt] = 0; qt++; }
+    }
 
     const double SPREAD_DECAY = 0.7;
     while (qh < qt) {
@@ -9524,6 +9554,13 @@ el_val_t engram_search_json(el_val_t query, el_val_t limit) {
                 EngramSemEntry* sem = qv ? malloc((size_t)g->node_count * sizeof(EngramSemEntry)) : NULL;
                 int64_t nsem = 0;
                 int64_t nhits = 0;
+                /* Raw (unfloored) cosine top-K, kept for the graph leg's
+                 * semantic seeds. Selected in THIS pass so the cosine is
+                 * computed exactly once per node — the seeding costs no extra
+                 * pass over the corpus and no extra embed round-trip. */
+                int64_t semseed[ENGRAM_EMBED_SEED_K];
+                double  semseedc[ENGRAM_EMBED_SEED_K];
+                int64_t nsemseed = 0;
                 for (int64_t i = 0; i < g->node_count; i++) {
                     EngramNode* n = &g->nodes[i];
                     /* Filter transparent layers — same as engram_search. */
@@ -9535,9 +9572,29 @@ el_val_t engram_search_json(el_val_t query, el_val_t limit) {
                         hits[nhits].salience = n->salience;
                         nhits++;
                     }
-                    if (sem) {
-                        double sv = eg_sem_term(n, qv, qdim);
-                        if (sv > 0.0) { sem[nsem].idx = i; sem[nsem].sem = sv; nsem++; }
+                    if (sem && n->emb && n->emb_dim == qdim) {
+                        double c = eg_cosine(n->emb, qv, qdim);
+                        /* Semantic leg: identical to eg_sem_term(), which is
+                         * left in place and still used by engram_search().
+                         * Inlined here only so one cosine serves both uses. */
+                        if (c > ENGRAM_EMBED_SEED_MIN) {
+                            double sv = (c - ENGRAM_EMBED_SEED_MIN) / (1.0 - ENGRAM_EMBED_SEED_MIN);
+                            if (sv > 1.0) sv = 1.0;
+                            sem[nsem].idx = i; sem[nsem].sem = sv; nsem++;
+                        }
+                        /* Graph seeds: top-K by RAW cosine, insertion-ordered. */
+                        if (c > 0.0 && (nsemseed < ENGRAM_EMBED_SEED_K
+                                        || c > semseedc[nsemseed - 1])) {
+                            int64_t p = nsemseed < ENGRAM_EMBED_SEED_K
+                                        ? nsemseed : ENGRAM_EMBED_SEED_K - 1;
+                            while (p > 0 && semseedc[p - 1] < c) {
+                                semseedc[p] = semseedc[p - 1];
+                                semseed[p]  = semseed[p - 1];
+                                p--;
+                            }
+                            semseedc[p] = c; semseed[p] = i;
+                            if (nsemseed < ENGRAM_EMBED_SEED_K) nsemseed++;
+                        }
                     }
                 }
                 qsort(hits, (size_t)nhits, sizeof(EngramRankEntry), engram_rank_cmp);
@@ -9549,7 +9606,8 @@ el_val_t engram_search_json(el_val_t query, el_val_t limit) {
                  * lexical ordering safe. */
                 EngramSemEntry* assoc = qv ? malloc((size_t)ENGRAM_ASSOC_MAX * sizeof(EngramSemEntry)) : NULL;
                 int64_t nassoc = assoc
-                    ? engram_assoc_leg(g, hits, nhits, qv, qdim, assoc, ENGRAM_ASSOC_MAX)
+                    ? engram_assoc_leg(g, hits, nhits, semseed, nsemseed,
+                                       qv, qdim, assoc, ENGRAM_ASSOC_MAX)
                     : 0;
                 int64_t* order = malloc((size_t)lim * sizeof(int64_t));
                 if (order) {