core/docs/evals
Shay 90fc1b40a0 docs(evals): articulation benchmark preamble — discourse-planner spine
Records the deterministic, grounded, multi-clause articulation
benchmark that the discourse-planner work has stabilised.  Mirrors
the format of teaching_loop_bench.md so the four sub-benches in
benchmarks/articulation.py have a load-bearing reference document.

Headline:

* 20 independent ChatRuntime instances × 4 prompts (EXPLAIN /
  PARAGRAPH / COMPOUND / WALKTHROUGH) produce 4 unique surfaces —
  byte-identical determinism on the articulation path with
  RuntimeConfig(discourse_planner=True).
* Every visible token traces to a pack lemma, pack gloss, reviewed
  teaching-chain entry, or fixed-template connective from the
  closed five-entry _MOVE_CONNECTIVE table.  No synthesis.
* discourse_planner sub-bench:
    cases:                     4
    articulate_sentence_rate:  1.0
    disclosure_sentence_rate:  0.0
    multi_sentence_rate:       1.0
* Compound prompt ("What is truth, and why does it matter?") emits
  6 distinct grounded sentences with cross-part fact dedup, no
  anchor repetition.
* Walkthrough mode walks the teaching-chain edge graph up to 3 hops,
  cycle-safe, final hop as CLOSURE; no chain ⇒ degrades to ANCHOR +
  SUPPORT rather than fabricating steps.

Doc explains the partitioned predicate contract
(articulate + disclosure + unarticulate = 1.0, total and disjoint)
so future readers know why ``multi_sentence_rate`` alone is not the
headline.

Companion docs cross-linked: discourse_runtime_baseline_2026-05-19.md
(lane-level delta table), the two new isolation lanes
(compound_intent_decomposition, walkthrough_chain), and the
partitioned multi_sentence_response contract.
2026-05-19 12:47:38 -07:00
..
assets
anti_regression_demo.md docs(adr-0055-0057): writeups + asciinema captures for the demo trilogy 2026-05-18 11:18:56 -07:00
articulation_bench_2026-05-19.md docs(evals): articulation benchmark preamble — discourse-planner spine 2026-05-19 12:47:38 -07:00
discourse_runtime_baseline_2026-05-19.md
learning_loop_demo.md
phase5_stratified_findings.md
phase6_comparative_demo.md
teaching_loop_bench.md