a719f1b58c
* feat(adr-0184): add semantic-state helper package * feat(adr-0184): add referent binding helpers * feat(adr-0184): add change cue helpers * refactor(adr-0184): use semantic-state helpers in accumulation * test(adr-0184): cover semantic-state helper guards
71 lines
2.2 KiB
Python
71 lines
2.2 KiB
Python
"""ADR-0184 S1 — conservative referent-binding helpers.
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These helpers are behavior-equivalent extractions from
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:mod:`generate.derivation.accumulate`. They are deliberately small: loose
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surface subject collection plus a refusal-first same-referent guard. They do
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not resolve ambiguous pronouns, do not gender-match, and do not choose the most
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recent actor. A new named subject is treated as a referent hazard by callers.
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"""
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from __future__ import annotations
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import re
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from typing import Final
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PRONOUNS: Final[frozenset[str]] = frozenset(
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{
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"he",
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"she",
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"they",
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"it",
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"him",
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"her",
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"them",
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"his",
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"hers",
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"its",
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"their",
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"we",
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"i",
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"you",
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}
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)
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_WORD_RE: Final[re.Pattern[str]] = re.compile(r"[A-Za-z]+")
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def leading_subject_token(clause: str) -> str | None:
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"""Return the clause's leading word token, or ``None`` if wordless.
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This is a loose signal collector, not a grammar parser. It mirrors the
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prior accumulation helper so S1 is behavior-equivalent.
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"""
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match = _WORD_RE.search(clause)
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return match.group(0) if match is not None else None
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def continues_anchor_referent(clause: str, anchor_subject: str | None) -> bool:
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"""Whether ``clause`` can safely continue ``anchor_subject``.
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Conservative ADR-0184 rule, extracted from accumulation:
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* no leading token: no new actor signal, so allow;
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* leading pronoun: allow as a continuation candidate;
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* same leading subject as the anchor: allow;
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* any other capitalized leading non-pronoun: new named actor, so disallow;
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* lowercase leading token: no named-actor signal, so allow.
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This does **not** prove pronoun resolution. Callers still gate the resulting
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candidate through grounding/completeness/pooling. Multi-actor ambiguity must
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be handled by future semantic-world logic, not by choosing a most-recent actor.
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"""
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subject = leading_subject_token(clause)
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if subject is None:
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return True
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if subject.lower() in PRONOUNS:
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return True
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if anchor_subject is not None and subject == anchor_subject:
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return True
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return not subject[:1].isupper()
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