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Ported unchanged from the internal scorer so published scores stay comparable.
Each checker returns ``{"is_valid": bool, ...}`` with diagnostic detail.
"""
from __future__ import annotations
import json
import re
from typing import Any
from .syllable import cal_syllable_count
HARD_CONSTRAINT_IDS = frozenset({
"format_preserve", "layout_break", "term_compliance",
"syllable_order", "social_preserve",
})
SOFT_CONSTRAINT_IDS = frozenset({
"style_consistency", "context_disambiguate", "coref_resolution",
"term_cross_sentence", "academic_format_preserve",
})
# ======================== Constraint text parsing ========================
def parse_term_targets(constraint_lines: list[str]) -> list[str]:
"""Target-side renderings from a `专名/术语对照: X→Y、...` line."""
target_terms = []
for line in constraint_lines:
if "术语对照" not in line and "专名" not in line:
continue
match = re.search(r"(?:专名/?)?术语对照[::]\s*(.*)", line)
if not match:
continue
for pair in re.split(r"[、,,]", match.group(1)):
if "→" in pair:
target = pair.split("→", 1)[1].strip()
if target:
target_terms.append(target)
return target_terms
def parse_layout_features(constraint_lines: list[str]) -> list[str]:
features = []
for line in constraint_lines:
if "布局" not in line and "排版" not in line:
continue
if "换行" in line:
features.append("newlines")
if "缩进" in line:
features.append("indent")
if "表格" in line:
features.append("table_align")
return features if features else ["newlines", "indent"]
def parse_social_elements(constraint_lines: list[str]) -> list[str]:
elements = []
for line in constraint_lines:
if "社交元素" not in line:
continue
for sep in (":", ":"):
if sep in line:
raw = line.split(sep, 1)[1].strip()
elements.extend(p.strip() for p in re.split(r"[、,,]", raw) if p.strip())
break
return elements
def collect_soft_constraint_descs(
constraint_ids: list[str], constraint_lines: list[str]
) -> dict[str, str]:
"""Map each soft constraint id to the prompt line stating it."""
keyword_map = {
"style_consistency": ["语体", "风格"],
"context_disambiguate": ["歧义", "消歧"],
"coref_resolution": ["指代", "代词"],
"term_cross_sentence": ["跨句", "全文统一"],
"academic_format_preserve": ["学术", "LaTeX", "学术格式"],
}
soft_descs: dict[str, str] = {}
for cid in constraint_ids:
if cid not in SOFT_CONSTRAINT_IDS:
continue
for line in constraint_lines:
if any(kw in line for kw in keyword_map.get(cid, [])):
soft_descs[cid] = line
break
soft_descs.setdefault(cid, cid)
return soft_descs
# ======================== Rule-based checkers ========================
def _build_term_pattern(term: str) -> str:
escaped = re.escape(term)
# CJK has no word boundaries; \b would never match against them.
if any(("一" <= ch <= "鿿") or ("" <= ch <= "ヿ") for ch in term):
return escaped
return rf"(?<!\w){escaped}(?!\w)"
def check_glossary(target_text: str, required_terms: list[str]) -> dict[str, Any]:
missing = [t for t in required_terms
if not re.search(_build_term_pattern(t), target_text)]
return {"is_valid": not missing, "missing_terms": missing}
def check_json_preserved(source_text: str, target_text: str) -> dict[str, Any]:
def extract_keys(text: str) -> tuple[bool, list[str]]:
try:
parsed = json.loads(text)
except json.JSONDecodeError:
return False, []
keys: list[str] = []
def walk(obj: Any, path: str = "") -> None:
if isinstance(obj, dict):
for key, value in obj.items():
current = f"{path}.{key}" if path else key
keys.append(current)
walk(value, current)
elif isinstance(obj, list):
for index, element in enumerate(obj):
walk(element, f"{path}[{index}]")
walk(parsed)
return True, keys
src_valid, src_keys = extract_keys(source_text)
tgt_valid, tgt_keys = extract_keys(target_text)
if not src_valid:
return {"is_valid": False, "issues": ["源文不是有效JSON"]}
if not tgt_valid:
return {"is_valid": False, "issues": ["译文不是有效JSON"]}
issues = []
missing = set(src_keys) - set(tgt_keys)
extra = set(tgt_keys) - set(src_keys)
if missing:
issues.append(f"缺失key: {missing}")
if extra:
issues.append(f"多余key: {extra}")
return {"is_valid": not issues, "issues": issues}
def _extract_visible_text(html: str) -> str:
return re.sub(r"<[^>]+>", "", html).strip()
def _chinese_ratio(text: str) -> float:
text = re.sub(r"\s+", "", text)
if not text:
return 0.0
return sum(1 for ch in text if "一" <= ch <= "鿿") / len(text)
def check_html_preserved(
source_text: str, target_text: str,
src_lang: str | None = None, tgt_lang: str | None = None,
) -> dict[str, Any]:
tag_pattern = re.compile(r"</?[a-z][a-z0-9]*\b[^>]*>", re.IGNORECASE)
src_tag_types = [re.sub(r"\s+.*?>", ">", t) for t in tag_pattern.findall(source_text)]
tgt_tag_types = [re.sub(r"\s+.*?>", ">", t) for t in tag_pattern.findall(target_text)]
issues = []
if src_tag_types != tgt_tag_types:
issues.append(f"标签不一致: 源文{len(src_tag_types)}个, 译文{len(tgt_tag_types)}个")
if src_lang == "zh" and tgt_lang not in ("ja", "zh"):
tgt_visible = _extract_visible_text(target_text)
if tgt_visible and _extract_visible_text(source_text):
ratio = _chinese_ratio(tgt_visible)
if ratio > 0.01:
issues.append(f"译文中残留中文(占比{ratio:.1%})")
return {"is_valid": not issues, "issues": issues}
def check_markdown_preserved(source_text: str, target_text: str) -> dict[str, Any]:
md_patterns = [
(r"^#{1,6}\s", "标题"), (r"\*\*[^*]+\*\*", "粗体"),
(r"\*[^*]+\*", "斜体"), (r"`[^`]+`", "行内代码"),
(r"```[\s\S]*?```", "代码块"), (r"^[-*+]\s", "列表项"),
(r"^\d+\.\s", "有序列表"), (r"\[.*?\]\(.*?\)", "链接"),
(r"!\[.*?\]\(.*?\)", "图片"), (r"^>\s", "引用"),
(r"\|.*\|", "表格"),
]
issues = []
for pattern, name in md_patterns:
if re.search(pattern, source_text, re.MULTILINE) and not re.search(
pattern, target_text, re.MULTILINE
):
issues.append(f"丢失{name}标记")
return {"is_valid": not issues, "issues": issues}
def check_placeholder_preserved(source_text: str, target_text: str) -> dict[str, Any]:
patterns = [
r"\{[a-zA-Z_][a-zA-Z0-9_]*\}",
r"%[dsf]",
r"\$\d+",
r"\{\{[a-zA-Z_][a-zA-Z0-9_]*\}\}",
]
issues = []
for pattern in patterns:
missing = set(re.findall(pattern, source_text)) - set(re.findall(pattern, target_text))
if missing:
issues.append(f"丢失占位符: {missing}")
return {"is_valid": not issues, "issues": issues}
def check_format_preserve(
source_text: str, target_text: str,
src_lang: str | None = None, tgt_lang: str | None = None,
) -> dict[str, Any]:
"""Dispatch to whichever format checkers the source text actually triggers."""
results: dict[str, Any] = {}
issues: list[str] = []
stripped = source_text.strip()
if stripped[:1] in ("{", "["):
try:
json.loads(stripped)
is_json = True
except json.JSONDecodeError:
is_json = False
if is_json:
sub = check_json_preserved(stripped, target_text.strip())
results["json"] = sub
if not sub["is_valid"]:
issues.extend(sub.get("issues", []))
if re.search(r"</?[a-z][a-z0-9]*\b[^>]*>", source_text, re.IGNORECASE):
sub = check_html_preserved(source_text, target_text, src_lang=src_lang, tgt_lang=tgt_lang)
results["html"] = sub
if not sub["is_valid"]:
issues.extend(sub.get("issues", []))
if re.search(r"^#{1,6}\s|\*\*|`|^[-*+]\s|^>\s|\[.*?\]\(.*?\)", source_text, re.MULTILINE):
sub = check_markdown_preserved(source_text, target_text)
results["markdown"] = sub
if not sub["is_valid"]:
issues.extend(sub.get("issues", []))
if re.search(
r"\{[a-zA-Z_][a-zA-Z0-9_]*\}|%[dsf]|\$\d+|\{\{[a-zA-Z_][a-zA-Z0-9_]*\}\}", source_text
):
sub = check_placeholder_preserved(source_text, target_text)
results["placeholder"] = sub
if not sub["is_valid"]:
issues.extend(sub.get("issues", []))
return {"is_valid": not issues, "issues": issues, "sub_results": results}
def check_layout_preserved(
source_text: str, target_text: str, layout_features: list[str] | None = None
) -> dict[str, Any]:
layout_features = layout_features or ["newlines", "indent"]
issues = []
if "newlines" in layout_features:
src_nl, tgt_nl = source_text.count("\n"), target_text.count("\n")
if src_nl != tgt_nl:
issues.append(f"换行数不一致: 源文{src_nl}, 译文{tgt_nl}")
if "indent" in layout_features:
src_indent = len(source_text) - len(source_text.lstrip())
tgt_indent = len(target_text) - len(target_text.lstrip())
if (src_indent > 0) != (tgt_indent > 0):
issues.append("缩进风格不一致")
if "table_align" in layout_features:
src_has = any("|" in l and l.count("|") >= 2 for l in source_text.splitlines())
tgt_has = any("|" in l and l.count("|") >= 2 for l in target_text.splitlines())
if src_has and not tgt_has:
issues.append("源文含表格对齐结构但译文丢失")
return {"is_valid": not issues, "issues": issues}
def check_social_preserve(target_text: str, elements: list[str]) -> dict[str, Any]:
if not elements:
return {"is_valid": True, "note": "no elements to check"}
missing = [e for e in elements if e not in target_text]
return {"is_valid": not missing, "missing_elements": missing}
def check_syllable_order(
prediction: str, durations: list[float], tgt_lang: str
) -> dict[str, Any]:
"""Rank-correlate per-sentence duration against translated syllable count.
Passes at concordance >= 0.9. Pairs with equal durations, and pairs with equal
syllable counts, are not counted as inversions.
"""
if not durations or not prediction:
return {"is_valid": True, "note": "no duration data"}
try:
output = json.loads(prediction)
except (json.JSONDecodeError, TypeError):
return {"is_valid": False, "note": "output is not valid JSON"}
if not isinstance(output, dict):
return {"is_valid": False, "note": "output is not a JSON object"}
syllables = [
cal_syllable_count(output.get(str(i), ""), tgt_lang)
for i in range(1, len(durations) + 1)
]
if len(syllables) < 2:
return {"is_valid": True, "note": "too few sentences"}
inversions = total_pairs = 0
for i in range(len(durations)):
for j in range(i + 1, len(durations)):
if durations[i] == durations[j]:
continue
total_pairs += 1
if syllables[i] == syllables[j]:
continue
if (durations[i] > durations[j]) != (syllables[i] > syllables[j]):
inversions += 1
if total_pairs == 0:
return {"is_valid": True, "note": "all durations equal"}
concordance = 1.0 - inversions / total_pairs
return {
"is_valid": concordance >= 0.9,
"concordance": round(concordance, 3),
"inversions": inversions,
"total_pairs": total_pairs,
}
def check_hard_constraints(row: dict[str, Any], prediction: str) -> dict[str, Any]:
"""Run every hard checker this instance is annotated for."""
if not prediction:
return {}
source_text = row["source_text"]
constraint_lines = row["constraints"]
results: dict[str, Any] = {}
for cid in row["constraint_ids"]:
if cid not in HARD_CONSTRAINT_IDS:
continue
if cid == "format_preserve":
results[cid] = check_format_preserve(
source_text, prediction,
src_lang=row["source_lang"], tgt_lang=row["target_lang"],
)
elif cid == "layout_break":
results[cid] = check_layout_preserved(
source_text, prediction, parse_layout_features(constraint_lines))
elif cid == "term_compliance":
terms = parse_term_targets(constraint_lines)
results[cid] = (check_glossary(prediction, terms) if terms
else {"is_valid": True, "note": "no terms to check"})
elif cid == "syllable_order":
results[cid] = check_syllable_order(
prediction, row.get("duration_s", []), row["target_lang"])
elif cid == "social_preserve":
results[cid] = check_social_preserve(
prediction, parse_social_elements(constraint_lines))
return results
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