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2e511b5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 | """Refusal detection, value resolution, and the cleaning provenance format."""
import json
import pytest
from legex.evaluation.comparison import classify_cell, normalise, refusal_reason, resolve
from legex.evaluation.cleaning import format_comment, format_original_input
REFUSALS = [
("The document does not state a specific date. N/A", "trial_start_date"),
("None (the judgment does not contain a party designation block)", "plaintiffs_all_count"),
("Based on my review, I cannot determine the amount in dispute.", "dispute_value_nominal"),
("N/A", "trial_end_date"),
("not specified", "trial_start_date"),
]
KEEPERS = [
("nonpecuniary", "dispute_value_nominal"),
("no_allocation_possible", "plaintiff_no1_ISIC1_industry_category"),
("Employment_Law/Discrimination", "legal_subject_judgement"),
("2024-01-21", "trial_end_date"),
("25400000", "dispute_value_nominal"),
("1", "plaintiffs_all_count"),
("1.0", "plaintiff_loosing_share"), # already a clean float → kept as-is
("0.86", "plaintiff_loosing_share"),
("l_financial_insurance", "defendant_no1_ISIC1_industry_category"),
]
# (raw, column, expected canonical) — a single value recoverable after stripping
# formatting noise / citations / backticks (never a digit scraped from prose).
RECOVERABLE = [
("20'000", "court_cost_awarded_nominal", "20000"),
("1 000 000", "dispute_value_nominal", "1000000"),
("2024/01/21", "trial_end_date", "2024-01-21"),
("1\n```", "plaintiffs_all_count", "1"),
("[1]\n\n2025-08-19", "trial_end_date", "2025-08-19"),
("1950\n[1] [2]", "court_cost_awarded_nominal", "1950"),
# 2026-08 Harvey run: standalone English prose dates despite YYYY-MM-DD rule.
("March 19, 2026", "trial_end_date", "2026-03-19"),
("30 September 2020", "trial_end_date", "2020-09-30"),
# 2026-08 Harvey run: ISIC codes with the sector letter capitalised.
("L_financial_insurance", "defendant_no1_ISIC1_industry_category", "l_financial_insurance"),
("No_allocation_possible", "plaintiff_no1_ISIC1_industry_category", "no_allocation_possible"),
# Currency-decorated clean amounts.
("CHF 9'728'400.00", "dispute_value_nominal", "9728400"),
("30'000.--", "dispute_value_nominal", "30000"),
("6'500 fr.", "court_cost_awarded_nominal", "6500"),
("22.201,76 EUR", "dispute_value_nominal", "22201.76"),
]
# Prose (has letters) → never auto-recovered, even with a number present → review.
PROSE_TO_REVIEW = [
("1.0\n\nThe complaint was declared inadmissible.", "plaintiff_loosing_share"),
("The operative part imposes court costs of 800 Swiss Francs.[1]\n\n800",
"court_cost_awarded_nominal"),
("Greer (No. 19-8709): 1.0\n\nGary (No. 20-444): 1.0", "plaintiff_loosing_share"),
# A number with a parenthetical qualifier is still prose — a human decides.
("1 (total plaintiffs/claimants/appellants)", "plaintiffs_all_count"),
]
# Grouped integers without a decimal part: thousands- vs decimal-separator is
# ambiguous ('5.000 €' = 5000 EU or 5.0 US) → review, never auto-recovered.
AMBIGUOUS_AMOUNTS_TO_REVIEW = [
("5.000 €", "dispute_value_nominal"),
("538,183 euro", "dispute_value_nominal"),
]
@pytest.mark.parametrize("text,col", REFUSALS)
def test_refusals_go_to_review(text, col):
status, _, reason = resolve(text, col)
assert status == "review" and reason
@pytest.mark.parametrize("text,col", KEEPERS)
def test_valid_values_kept(text, col):
status, value, _ = resolve(text, col)
assert status == "valid" and value == text
@pytest.mark.parametrize("text,col,canon", RECOVERABLE)
def test_recoverable_values_canonicalised(text, col, canon):
status, value, _ = resolve(text, col)
assert status == "recovered" and value == canon
# Formatting-only recoveries the scorer already parses identically → must be score-neutral.
# (Noise-stripped dates like "[1]\n\n2025-08-19" are intentional corrections, not neutral.)
NEUTRAL_RECOVERABLE = [
("20'000", "court_cost_awarded_nominal", "20000"),
("1 000 000", "dispute_value_nominal", "1000000"),
("2024/01/21", "trial_end_date", "2024-01-21"),
("1\n```", "plaintiffs_all_count", "1"),
("1950\n[1] [2]", "court_cost_awarded_nominal", "1950"),
]
@pytest.mark.parametrize("text,col,canon", NEUTRAL_RECOVERABLE)
def test_recovery_is_score_neutral(text, col, canon):
for gold in ("", canon, "999", "2024-01-21"):
assert classify_cell(gold, normalise(text), col) == classify_cell(gold, canon, col)
@pytest.mark.parametrize("text,col", PROSE_TO_REVIEW)
def test_prose_with_number_goes_to_review_not_garbage(text, col):
# Never scrape a number out of prose into the data — a human decides.
status, _, _ = resolve(text, col)
assert status == "review"
@pytest.mark.parametrize("text,col", AMBIGUOUS_AMOUNTS_TO_REVIEW)
def test_ambiguous_grouped_amounts_go_to_review(text, col):
status, _, _ = resolve(text, col)
assert status == "review"
def test_prose_without_value_or_marker_still_reviewed():
status, _, reason = resolve(
"Based on the decision, the respondent substantially prevailed on the merits.",
"plaintiff_loosing_share",
)
assert status == "review" and reason == "no recoverable value"
def test_normalise_is_pure():
assert normalise("The document does not state a date. N/A") != ""
assert refusal_reason("nonpecuniary", "dispute_value_nominal") is None
def test_provenance_format():
changes = {
"trial_start_date": ("Not specified ", ""),
"court_cost_awarded_nominal": ("20'000", "20000"),
}
assert format_comment(changes) == (
"The trial_start_date was sanitized from 'Not specified ' to 'empty (removed)'. "
"The court_cost_awarded_nominal was sanitized from '20'000' to '20000'."
)
assert json.loads(format_original_input(changes)) == {
"trial_start_date": "Not specified ", "court_cost_awarded_nominal": "20'000",
}
assert format_comment({}) is None
assert format_original_input({}) == "{}"
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