feat(manifold): add outcome compatibility guard and conditional market rejection
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Reject false-positive matches where Jaccard overlap is high but the outcome is
not equivalent (e.g. Poly nomination vs Manifold "If X is nominee, will he win").

- _is_conditional(): detect conditional Manifold markets (If/Conditional on/
  Assuming/Given that prefixes + mid-sentence " if ...," clauses) -> reject with
  reason "conditional_market".
- _classify_outcome(): classify into nomination|primary_win|general_win|
  conditional|other; reject when poly/mfld types differ or either is conditional
  -> reason "outcome_mismatch: poly=... manifold=...".
- Persist poly_outcome_type/mfld_outcome_type on ManifoldMatchResult, in
  manifold_match_audit (CREATE + idempotent ALTER), save_manifold_audit() and
  the bayesian call site.
- Tests covering classification, conditional detection and the Graham Platner
  regression (now rejected); valid nomination<->nomination still accepted.

Untouched: _MATCH_THRESHOLD (0.40), MANIFOLD_LOGODDS_WEIGHT, edge thresholds,
exposure, trading logic.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
chemavx
2026-05-31 15:28:26 +00:00
parent d51d47c921
commit 34fd1f8719
5 changed files with 253 additions and 10 deletions
+6 -2
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@@ -530,6 +530,8 @@ class Database:
match_score: Optional[float],
match_reason: Optional[str],
match_status: str,
poly_outcome_type: Optional[str] = None,
mfld_outcome_type: Optional[str] = None,
) -> None:
async with self._pool.acquire() as conn:
await conn.execute("""
@@ -537,13 +539,15 @@ class Database:
id, poly_market_id, poly_question, search_query,
mfld_market_id, mfld_market_title, mfld_market_url,
prob_raw, prob_final, inverted,
match_score, match_reason, match_status, used_in_trade
) VALUES ($1,$2,$3,$4,$5,$6,$7,$8,$9,$10,$11,$12,$13,FALSE)
match_score, match_reason, match_status, used_in_trade,
poly_outcome_type, mfld_outcome_type
) VALUES ($1,$2,$3,$4,$5,$6,$7,$8,$9,$10,$11,$12,$13,FALSE,$14,$15)
""",
audit_id, poly_market_id, poly_question, search_query,
mfld_market_id, mfld_market_title, mfld_market_url,
prob_raw, prob_final, inverted,
match_score, match_reason, match_status,
poly_outcome_type, mfld_outcome_type,
)
async def mark_manifold_audit_used(self, audit_id: str) -> None:
+86 -7
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@@ -6,6 +6,15 @@ by keyword overlap and returns a ManifoldMatchResult with full audit metadata.
Match threshold: >= 0.40 Jaccard overlap (raised from 0.25 for stricter semantics).
Outcome compatibility guard (conservative):
- Conditional Manifold markets ("If X, will Y?" / "Conditional on..." / "Assuming..."
/ "Given that..." / mid-sentence "...if X is nominated, will...") are rejected:
a premise-gated question is not equivalent to a direct outcome question even when
token overlap is high. reason='conditional_market'.
- Each side is classified into an outcome_type (nomination | primary_win |
general_win | conditional | other). Matches with differing outcome_type — or any
conditional side — are rejected. reason='outcome_mismatch: poly=... manifold=...'.
Inversion guard (conservative):
- If Polymarket question names a party (democrat/republican) AND the matched
Manifold market names the OPPOSITE party → invert probability (1 - prob).
@@ -59,6 +68,8 @@ class ManifoldMatchResult:
match_reason: Optional[str] = None # human-readable explanation
inverted: bool = False
search_query: str = ""
poly_outcome_type: Optional[str] = None # nomination|primary_win|general_win|conditional|other
mfld_outcome_type: Optional[str] = None
def _significant_words(text: str) -> set[str]:
@@ -82,6 +93,45 @@ def _detect_party(text: str) -> Optional[str]:
return None
# ── Conditional-market detection (Task 1) ──────────────────────────────────────
# A market is "conditional" when its resolution is gated on a premise rather than
# asking the outcome directly (e.g. "If X is the nominee, will he win?"). Such a
# market is NOT equivalent to a direct outcome question even with high token overlap.
_CONDITIONAL_PREFIXES = ("if ", "conditional on", "assuming ", "given that")
# " if <clause>," — a mid-sentence conditional clause closed by a comma.
_CONDITIONAL_CLAUSE_RE = re.compile(r"\sif\s[^,]*,")
def _is_conditional(text: str) -> bool:
"""True if the question is phrased conditionally (premise-gated)."""
t = (text or "").strip().lower()
if t.startswith(_CONDITIONAL_PREFIXES):
return True
return bool(_CONDITIONAL_CLAUSE_RE.search(t))
def _classify_outcome(text: str) -> str:
"""
Coarse classification of what a question is *asking about*, used to reject
matches whose outcomes are not equivalent even when tokens overlap.
Returns one of: nomination | primary_win | general_win | conditional | other.
Order matters: conditional is checked first (premise-gated), then nomination
(which subsumes "primary nominee"), then primary, then general election.
"""
t = (text or "").strip().lower()
if t.startswith(_CONDITIONAL_PREFIXES):
return "conditional"
if any(k in t for k in ("nominee", "nominated", "nomination")):
return "nomination"
if any(k in t for k in ("primary", "win the primary", "first round")):
return "primary_win"
if any(k in t for k in ("win the election", "win the race",
"win the seat", "general election")):
return "general_win"
return "other"
def _find_best_candidate(poly_question: str, results: list[dict]) -> tuple[Optional[dict], float]:
"""Find the highest-scoring open binary Manifold market by Jaccard overlap."""
poly_words = _significant_words(poly_question)
@@ -137,9 +187,14 @@ class ManifoldClient:
if cached and (now - cached[0]) < CACHE_TTL_SEC:
return cached[1]
poly_outcome = _classify_outcome(question)
query = _build_search_query(question)
if not query:
result = ManifoldMatchResult(status="no_results", search_query="")
result = ManifoldMatchResult(
status="no_results", search_query="",
poly_outcome_type=poly_outcome,
)
self._cache[question] = (now, result)
return result
@@ -152,12 +207,18 @@ class ManifoldClient:
results = resp.json()
except Exception as exc:
log.warning("Manifold API error for %r: %s", question[:40], exc)
result = ManifoldMatchResult(status="no_results", search_query=query)
result = ManifoldMatchResult(
status="no_results", search_query=query,
poly_outcome_type=poly_outcome,
)
self._cache[question] = (now, result)
return result
if not results:
result = ManifoldMatchResult(status="no_results", search_query=query)
result = ManifoldMatchResult(
status="no_results", search_query=query,
poly_outcome_type=poly_outcome,
)
self._cache[question] = (now, result)
return result
@@ -176,22 +237,36 @@ class ManifoldClient:
match_score=score if best else None,
match_reason=reason,
search_query=query,
poly_outcome_type=poly_outcome,
mfld_outcome_type=_classify_outcome(best.get("question", "")) if best else None,
)
self._cache[question] = (now, result)
return result
# ── Inversion analysis (conservative) ────────────────────────────────
# ── Outcome compatibility + inversion analysis (conservative) ─────────
mfld_title = best.get("question", "")
mfld_outcome = _classify_outcome(mfld_title)
poly_party = _detect_party(question)
manifold_party = _detect_party(best.get("question", ""))
manifold_party = _detect_party(mfld_title)
poly_words = _significant_words(question)
mfld_words = _significant_words(best.get("question", ""))
mfld_words = _significant_words(mfld_title)
matched_tokens = sorted(poly_words & mfld_words)[:6]
inverted = False
rejection_reason: Optional[str] = None
if poly_party is not None:
# Task 1 — conditional Manifold market is never equivalent to a direct
# outcome question, regardless of token overlap.
if _is_conditional(mfld_title):
rejection_reason = "conditional_market: manifold question is conditional"
# Task 2 — outcome types must match; any conditional side is rejected.
elif (poly_outcome == "conditional" or mfld_outcome == "conditional"
or poly_outcome != mfld_outcome):
rejection_reason = (
f"outcome_mismatch: poly={poly_outcome} manifold={mfld_outcome}"
)
elif poly_party is not None:
if manifold_party is None:
# Poly specifies a party; Manifold does not → can't verify inversion safety
rejection_reason = (
@@ -219,6 +294,8 @@ class ManifoldClient:
f"jaccard={score:.2f}, tokens={matched_tokens}, {rejection_reason}"
),
search_query=query,
poly_outcome_type=poly_outcome,
mfld_outcome_type=mfld_outcome,
)
self._cache[question] = (now, result)
return result
@@ -257,6 +334,8 @@ class ManifoldClient:
match_reason=match_reason,
inverted=inverted,
search_query=query,
poly_outcome_type=poly_outcome,
mfld_outcome_type=mfld_outcome,
)
self._cache[question] = (now, result)
return result
+7 -1
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@@ -207,13 +207,19 @@ CREATE TABLE IF NOT EXISTS manifold_match_audit (
match_score DOUBLE PRECISION,
match_reason TEXT,
match_status TEXT NOT NULL,
used_in_trade BOOLEAN DEFAULT FALSE
used_in_trade BOOLEAN DEFAULT FALSE,
poly_outcome_type TEXT,
mfld_outcome_type TEXT
);
CREATE INDEX IF NOT EXISTS idx_mfld_audit_timestamp ON manifold_match_audit(timestamp DESC);
CREATE INDEX IF NOT EXISTS idx_mfld_audit_status ON manifold_match_audit(match_status);
CREATE INDEX IF NOT EXISTS idx_mfld_audit_poly_mkt ON manifold_match_audit(poly_market_id);
-- Backfill outcome-type columns on pre-existing tables (idempotent).
ALTER TABLE manifold_match_audit ADD COLUMN IF NOT EXISTS poly_outcome_type TEXT;
ALTER TABLE manifold_match_audit ADD COLUMN IF NOT EXISTS mfld_outcome_type TEXT;
-- ─────────────────────────────────────────────────────────────────────────────
-- Metric exclusion — administrative closure flag
--
+2
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@@ -470,6 +470,8 @@ class BayesianStrategy:
match_score=manifold_result.match_score,
match_reason=manifold_result.match_reason,
match_status=manifold_result.status,
poly_outcome_type=manifold_result.poly_outcome_type,
mfld_outcome_type=manifold_result.mfld_outcome_type,
)
except Exception as exc:
log.warning("Failed to save manifold audit: %s", exc)
+152
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@@ -0,0 +1,152 @@
"""
Tests for the Manifold outcome-compatibility guard.
Regression: a Polymarket *nomination* question must not match a Manifold
*conditional* question ("If X is the nominee, will he win?") even at Jaccard=1.0.
"""
import asyncio
import pytest
from bot.data.manifold import (
ManifoldClient,
_classify_outcome,
_is_conditional,
)
# ── _is_conditional ────────────────────────────────────────────────────────────
def test_is_conditional_prefixes():
assert _is_conditional("If Graham Platner is the nominee, will he win?")
assert _is_conditional("Conditional on a recession, will rates fall?")
assert _is_conditional("Assuming Trump runs, will he win?")
assert _is_conditional("Given that X happens, will Y?")
def test_is_conditional_midsentence_clause():
assert _is_conditional("Will Biden, if he is nominated, win the election?")
def test_is_not_conditional():
assert not _is_conditional("Will Graham Platner be the Democratic nominee?")
assert not _is_conditional("Will the GOP win the Senate?")
# "if" without a closing comma clause is not flagged
assert not _is_conditional("What happens if everything goes right")
# ── _classify_outcome ───────────────────────────────────────────────────────────
def test_classify_nomination():
assert _classify_outcome("Will X be the Democratic nominee for Senate?") == "nomination"
assert _classify_outcome("Will X be nominated?") == "nomination"
# "primary nominee" → nomination (checked before primary)
assert _classify_outcome("Will X be the primary nominee?") == "nomination"
def test_classify_primary_win():
assert _classify_outcome("Will X win the primary?") == "primary_win"
assert _classify_outcome("Will X advance in the first round?") == "primary_win"
def test_classify_general_win():
assert _classify_outcome("Will X win the election?") == "general_win"
assert _classify_outcome("Will X win the seat?") == "general_win"
assert _classify_outcome("Will X win the general election?") == "general_win"
def test_classify_conditional():
assert _classify_outcome("If X is the nominee, will he win?") == "conditional"
assert _classify_outcome("Assuming a runoff, who wins?") == "conditional"
def test_classify_other():
assert _classify_outcome("Will it rain tomorrow?") == "other"
# ── End-to-end get_match with a stubbed Manifold API ────────────────────────────
class _StubResponse:
def __init__(self, payload):
self._payload = payload
def raise_for_status(self):
pass
def json(self):
return self._payload
class _StubHTTP:
def __init__(self, payload):
self._payload = payload
async def get(self, *args, **kwargs):
return _StubResponse(self._payload)
async def aclose(self):
pass
async def _match(poly, mfld_market):
client = ManifoldClient()
client._client = _StubHTTP([mfld_market])
try:
return await client.get_match(poly)
finally:
await client.close()
def test_graham_platner_conditional_rejected():
"""Poly nomination vs Manifold conditional → rejected (Task 4.1)."""
poly = ("Will Graham Platner be the Democratic nominee for Senate "
"in Maine in 2026?")
mfld_market = {
"outcomeType": "BINARY",
"probability": 0.55,
"question": ("If Graham Platner is the Democratic nominee for Senate "
"in Maine, will he win the general election?"),
"id": "abc123",
"slug": "graham-platner-win",
"creatorUsername": "someone",
}
result = asyncio.run(_match(poly, mfld_market))
assert result.status == "rejected"
assert result.match_reason is not None
assert ("conditional" in result.match_reason
or "outcome_mismatch" in result.match_reason)
# outcome types are classified and available for persistence
assert result.poly_outcome_type == "nomination"
assert result.mfld_outcome_type == "conditional"
def test_outcome_mismatch_nomination_vs_general_rejected():
"""Poly nomination vs Manifold general_win (non-conditional) → rejected."""
poly = "Will Jane Doe be the Republican nominee for Governor?"
mfld_market = {
"outcomeType": "BINARY",
"probability": 0.4,
"question": "Will Jane Doe win the election for Governor?",
"id": "x", "slug": "jane-doe", "creatorUsername": "u",
}
result = asyncio.run(_match(poly, mfld_market))
assert result.status == "rejected"
assert "outcome_mismatch" in result.match_reason
assert result.poly_outcome_type == "nomination"
assert result.mfld_outcome_type == "general_win"
def test_matching_nomination_accepted():
"""Poly nomination vs Manifold nomination (same outcome) → accepted."""
poly = "Will Graham Platner be the Democratic nominee for Senate in Maine?"
mfld_market = {
"outcomeType": "BINARY",
"probability": 0.62,
"question": "Will Graham Platner be the Democratic Senate nominee in Maine?",
"id": "ok", "slug": "platner-nominee", "creatorUsername": "u",
}
result = asyncio.run(_match(poly, mfld_market))
assert result.status == "accepted"
assert result.poly_outcome_type == "nomination"
assert result.mfld_outcome_type == "nomination"
assert result.prob_final == pytest.approx(0.62)