File size: 17,604 Bytes
e63569d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e8412e3
 
 
 
e63569d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e8412e3
e63569d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8c50d16
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
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
"""Deterministic label repairs for known weak-label blind spots."""

from __future__ import annotations

import re
from dataclasses import dataclass
from typing import Dict, Iterable, List, Optional, Sequence, Tuple


SEPARATOR_CHARS = set(" \t-_.|~~")

ROMAN_NUMERAL_VALUES = {
    "II": 2,
    "III": 3,
    "IV": 4,
    "V": 5,
    "VI": 6,
    "VII": 7,
    "VIII": 8,
    "IX": 9,
    "Ⅱ": 2,
    "Ⅲ": 3,
    "Ⅳ": 4,
    "Ⅴ": 5,
    "Ⅵ": 6,
    "Ⅶ": 7,
    "Ⅷ": 8,
    "Ⅸ": 9,
}

CN_NUMERAL_VALUES = {
    "一": 1,
    "二": 2,
    "兩": 2,
    "两": 2,
    "貳": 2,
    "贰": 2,
    "弐": 2,
    "弍": 2,
    "三": 3,
    "參": 3,
    "叁": 3,
    "参": 3,
    "四": 4,
    "肆": 4,
    "五": 5,
    "伍": 5,
    "六": 6,
    "陸": 6,
    "陆": 6,
    "七": 7,
    "柒": 7,
    "八": 8,
    "捌": 8,
    "九": 9,
    "玖": 9,
    "十": 10,
}

READING_MARKER_VALUES = {
    "ni no sara": 2,
    "ni no shou": 2,
    "ni no sho": 2,
    "ni no syo": 2,
    "ni no shō": 2,
    "ni gakki": 2,
    "sono ni": 2,
    "san no sara": 3,
    "san no shou": 3,
    "san no sho": 3,
    "san no syo": 3,
    "yon no sara": 4,
    "shi no sara": 4,
    "shin no sara": 4,
    "go no sara": 5,
    "gou no sara": 5,
}

# Bare "Ni" is often the Japanese particle に in romanized titles. Only repair
# it for titles that have been verified as a sequel marker in the release name.
STANDALONE_NI_SEASON_BASES = {
    "Kakuriyo no Yadomeshi": 2,
}

EPISODE_CONTEXT_RE = re.compile(
    r"^\s*(?:"
    r"[-_]\s*(?:\d{1,4}|NCOP|NCED|OP|ED|OVA|OAD|SP|END)\b|"
    r"#\s*\d{1,4}|"
    r"[\[\(【《]\s*(?:EP?|#)?\d{1,4}"
    r")",
    re.I,
)

EPISODE_SPAN_RE = re.compile(
    r"(?:"
    r"[Ss]\d{1,2}[Ee]\d{1,4}(?:v\d+)?|"
    r"(?:^|[\s._])[-_]\s*\d{1,4}(?:v\d+)?(?=$|[\s._\-\]\)】》\[])|"
    r"[\[\(【《](?:EP?|#)?\d{1,4}(?:v\d+)?[\]\)】》]|"
    r"(?:^|[\s._\-\[\(【《#])(?:EP?|第|#)\d{1,4}(?:v\d+)?(?:[话話集])?(?=$|[\s._\-\]\)】》])"
    r")",
    re.I,
)
BRACKET_RE = re.compile(r"\[([^\]]*)\]|\(([^)]*)\)|【([^】]*)】|《([^》]*)》")
RESOLUTION_RE = re.compile(r"(?<![A-Za-z0-9])(?:\d{3,4}[pP]|\d[Kk]|\d{3,4}[xX×]\d{3,4})(?![A-Za-z0-9])")
SOURCE_TOKEN_PATTERN = (
    r"WEB[-_ ]?DL|WEB[-_ ]?Rip|BDRip|BluRay|BDMV|BD|DVDRip|DVD|TVRip|HDTV|"
    r"Netflix|NF|AMZN|Baha|CR|ABEMA|DSNP|U[-_ ]?NEXT|Hulu|AT[-_ ]?X|"
    r"x26[45]|h\.?26[45]|HEVC|AVC|AV1|AAC\d*(?:\.\d+)?|AAC|FLAC|MP3|DTS|Opus|"
    r"CHS|CHT|GB|BIG5|JPN?|JPSC|JPTC|繁中|简中"
)
SOURCE_RE = re.compile(rf"(?<![A-Za-z0-9])(?:{SOURCE_TOKEN_PATTERN})(?![A-Za-z0-9])", re.I)
SOURCE_TAG_RE = re.compile(
    rf"^(?:{SOURCE_TOKEN_PATTERN})(?:\s*(?:[&+/,_-]|,\s*)\s*(?:{SOURCE_TOKEN_PATTERN}))*$",
    re.I,
)
SPECIAL_TAG_RE = re.compile(
    r"^(?:檢索|检索|搜索|搜寻|搜尋|别名|別名|alias|search|keyword)\s*[::].+",
    re.I,
)
SPECIAL_CODE_RE = re.compile(
    r"^(?:NCOP|NCED|OP|ED|PV|CM)\d*$|^IV\d+$|^(?:OVA|OAD|SP)\d*$",
    re.I,
)

READING_MARKER_RE = re.compile(
    r"(?<![A-Za-z0-9])"
    r"(?P<marker>"
    r"Ni\s+no\s+(?:Sara|Shou|Sho|Syo|Shō)|"
    r"San\s+no\s+(?:Sara|Shou|Sho|Syo)|"
    r"(?:Yon|Shi|Shin)\s+no\s+Sara|"
    r"(?:Go|Gou)\s+no\s+Sara|"
    r"Ni\s+Gakki|"
    r"Sono\s+Ni"
    r")"
    r"(?![A-Za-z0-9])",
)

ROMAN_MARKER_RE = re.compile(
    r"(?<![A-Za-z0-9])"
    r"(?P<marker>II|III|IV|V|VI|VII|VIII|IX|[ⅡⅢⅣⅤⅥⅦⅧⅨ])"
    r"(?![A-Za-z0-9])"
)

CJK_MARKER_RE = re.compile(
    r"(?P<marker>"
    r"[一二三四五六七八九十兩两貳贰弐弍參叁参肆伍陸陆柒捌玖](?:\s*(?:ノ|の|之)\s*(?:章|期|季|部))?|"
    r"第[一二三四五六七八九十兩两貳贰弐弍參叁参肆伍陸陆柒捌玖\d]+[季期部章]"
    r")"
)


@dataclass(frozen=True)
class LabelRepair:
    kind: str
    marker: str
    value: int
    start: int
    end: int


def clean_marker_text(text: str) -> str:
    return text.strip().strip("[]()【】《》()").strip()


def cn_number_to_int(text: str) -> Optional[int]:
    text = text.strip()
    if text.isdigit():
        return int(text)
    if text in CN_NUMERAL_VALUES:
        return CN_NUMERAL_VALUES[text]
    values = CN_NUMERAL_VALUES
    if text.startswith("十") and len(text) == 2:
        return 10 + values.get(text[1], 0)
    if text.endswith("十") and len(text) == 2:
        return values.get(text[0], 0) * 10
    if "十" in text and len(text) == 3:
        return values.get(text[0], 0) * 10 + values.get(text[2], 0)
    return None


def season_marker_number(text: str) -> Optional[int]:
    """Return season number for compact sequel markers such as II or Ni no Sara."""
    clean = clean_marker_text(text)
    if not clean:
        return None

    if clean in ROMAN_NUMERAL_VALUES:
        return ROMAN_NUMERAL_VALUES[clean]

    lowered = re.sub(r"\s+", " ", clean.lower()).strip()
    if lowered in READING_MARKER_VALUES:
        return READING_MARKER_VALUES[lowered]
    if lowered == "ni":
        return 2

    explicit = re.fullmatch(r"第(.+)[季期部章]", clean)
    if explicit:
        return cn_number_to_int(explicit.group(1))

    cjk = re.fullmatch(r"([一二三四五六七八九十兩两貳贰弐弍參叁参肆伍陸陆柒捌玖])(?:\s*(?:ノ|の|之)\s*(?:章|期|季|部))?", clean)
    if cjk:
        return cn_number_to_int(cjk.group(1))

    return None


def token_offsets_in_text(text: str, tokens: Sequence[str]) -> Optional[List[Tuple[int, int]]]:
    offsets: List[Tuple[int, int]] = []
    cursor = 0
    for token in tokens:
        if token == "":
            offsets.append((cursor, cursor))
            continue
        position = text.find(token, cursor)
        if position < 0:
            return None
        end = position + len(token)
        offsets.append((position, end))
        cursor = end
    return offsets


def has_episode_context(text: str, marker_end: int) -> bool:
    tail = text[marker_end:]
    if EPISODE_CONTEXT_RE.match(tail):
        return True

    # Some releases put a season marker at the end of a title bracket and the
    # episode in the next bracket: `[Title 貳之章][01]`.
    tail = tail.lstrip()
    tail = re.sub(r"^[\]\)】》]\s*", "", tail)
    tail = re.sub(
        r"^(?:[\[\(【《]\s*(?:menu|menus|bdmenu|ncop|nced|op|ed|ova|oad|sp)\s*[\]\)】》]\s*){0,2}",
        "",
        tail,
        flags=re.I,
    )
    return bool(EPISODE_CONTEXT_RE.match(tail))


def find_sequel_season_markers(text: str) -> List[LabelRepair]:
    """Find high-confidence sequel markers that should be labeled as SEASON."""
    repairs: List[LabelRepair] = []

    for pattern, kind in (
        (READING_MARKER_RE, "reading"),
        (ROMAN_MARKER_RE, "roman"),
        (CJK_MARKER_RE, "cjk"),
    ):
        for match in pattern.finditer(text):
            marker = match.group("marker")
            value = season_marker_number(marker)
            if value is None or not has_episode_context(text, match.end()):
                continue
            repairs.append(LabelRepair(kind, marker, value, match.start(), match.end()))

    for base, value in STANDALONE_NI_SEASON_BASES.items():
        pattern = re.compile(rf"(?<![A-Za-z0-9]){re.escape(base)}\s+(?P<marker>Ni)(?![A-Za-z0-9])")
        for match in pattern.finditer(text):
            if not has_episode_context(text, match.end("marker")):
                continue
            repairs.append(
                LabelRepair(
                    kind="verified_bare_ni",
                    marker=match.group("marker"),
                    value=value,
                    start=match.start("marker"),
                    end=match.end("marker"),
                )
            )

    repairs.sort(key=lambda item: (item.start, item.end))
    deduped: List[LabelRepair] = []
    for repair in repairs:
        if deduped and repair.start < deduped[-1].end:
            previous = deduped[-1]
            if (repair.end - repair.start) > (previous.end - previous.start):
                deduped[-1] = repair
            continue
        deduped.append(repair)
    return deduped


def labels_have_season_before(labels: Sequence[str], offsets: Sequence[Tuple[int, int]], marker_start: int) -> bool:
    return any(label.endswith("SEASON") and end <= marker_start for label, (_start, end) in zip(labels, offsets))


def token_indices_for_span(offsets: Sequence[Tuple[int, int]], start: int, end: int) -> List[int]:
    return [
        idx for idx, (tok_start, tok_end) in enumerate(offsets)
        if tok_start < end and tok_end > start
    ]


def label_span(labels: List[str], indices: Sequence[int], entity: str) -> None:
    previous_is_same_entity = bool(indices) and indices[0] > 0 and labels[indices[0] - 1].endswith(entity)
    first = not previous_is_same_entity
    for idx in indices:
        labels[idx] = f"B-{entity}" if first else f"I-{entity}"
        first = False


def label_span_if_changed(labels: List[str], indices: Sequence[int], entity: str) -> bool:
    previous_is_same_entity = bool(indices) and indices[0] > 0 and labels[indices[0] - 1].endswith(entity)
    first_label = f"I-{entity}" if previous_is_same_entity else f"B-{entity}"
    expected = [first_label] + [f"I-{entity}"] * max(0, len(indices) - 1)
    if [labels[idx] for idx in indices] == expected:
        return False
    label_span(labels, indices, entity)
    return True


def safe_to_overwrite_meta(labels: Sequence[str], indices: Sequence[int]) -> bool:
    if not indices:
        return False
    return not any(
        labels[idx].endswith(("GROUP", "EPISODE", "SEASON"))
        for idx in indices
    )


def mark_adjacent_title_separators_o(
    tokens: Sequence[str],
    labels: List[str],
    marker_indices: Sequence[int],
) -> None:
    if not marker_indices:
        return

    idx = marker_indices[0] - 1
    while idx >= 0 and "".join(tokens[idx]).strip() == "" and labels[idx].endswith("TITLE"):
        labels[idx] = "O"
        idx -= 1

    idx = marker_indices[-1] + 1
    while idx < len(tokens) and tokens[idx] in SEPARATOR_CHARS and labels[idx].endswith("TITLE"):
        labels[idx] = "O"
        idx += 1


def first_episode_end(labels: Sequence[str], offsets: Sequence[Tuple[int, int]], text: str) -> int:
    ends = [
        end for label, (_start, end) in zip(labels, offsets)
        if label.endswith("EPISODE")
    ]
    if ends:
        return min(ends)
    match = EPISODE_SPAN_RE.search(text)
    return match.end() if match else 0


def bracket_content_spans(text: str) -> Iterable[Tuple[str, int, int, int, int]]:
    for match in BRACKET_RE.finditer(text):
        groups = match.groups()
        group_index = next((idx for idx, value in enumerate(groups) if value is not None), None)
        if group_index is None:
            continue
        inner = groups[group_index] or ""
        # The opening delimiter is one code point in all supported bracket forms.
        inner_start = match.start() + 1
        inner_end = inner_start + len(inner)
        yield inner.strip(), inner_start, inner_end, match.start(), match.end()


def repair_structural_meta_labels(
    text: str,
    tokens: Sequence[str],
    labels: List[str],
    offsets: Sequence[Tuple[int, int]],
) -> List[LabelRepair]:
    repairs: List[LabelRepair] = []
    episode_end = first_episode_end(labels, offsets, text)

    for clean, inner_start, inner_end, bracket_start, _bracket_end in bracket_content_spans(text):
        if bracket_start < episode_end:
            continue
        if not clean:
            continue

        if SPECIAL_TAG_RE.fullmatch(clean) or SPECIAL_CODE_RE.fullmatch(clean):
            indices = token_indices_for_span(offsets, inner_start, inner_end)
            if safe_to_overwrite_meta(labels, indices) and label_span_if_changed(labels, indices, "SPECIAL"):
                repairs.append(LabelRepair("special", clean, 0, inner_start, inner_end))
            continue

        if SOURCE_TAG_RE.fullmatch(clean):
            indices = token_indices_for_span(offsets, inner_start, inner_end)
            if safe_to_overwrite_meta(labels, indices) and label_span_if_changed(labels, indices, "SOURCE"):
                repairs.append(LabelRepair("source", clean, 0, inner_start, inner_end))
            continue

        for match in RESOLUTION_RE.finditer(clean):
            start = inner_start + match.start()
            end = inner_start + match.end()
            indices = token_indices_for_span(offsets, start, end)
            if safe_to_overwrite_meta(labels, indices) and label_span_if_changed(labels, indices, "RESOLUTION"):
                repairs.append(LabelRepair("resolution", match.group(0), 0, start, end))

        for match in SOURCE_RE.finditer(clean):
            start = inner_start + match.start()
            end = inner_start + match.end()
            indices = token_indices_for_span(offsets, start, end)
            if safe_to_overwrite_meta(labels, indices) and label_span_if_changed(labels, indices, "SOURCE"):
                repairs.append(LabelRepair("source", match.group(0), 0, start, end))

    # Dot-separated WEB names often carry source/resolution after SxxEyy without
    # brackets. Repair only after the episode span to avoid touching titles.
    for pattern, entity in ((RESOLUTION_RE, "RESOLUTION"), (SOURCE_RE, "SOURCE")):
        for match in pattern.finditer(text):
            if match.start() < episode_end:
                continue
            indices = token_indices_for_span(offsets, match.start(), match.end())
            if safe_to_overwrite_meta(labels, indices) and label_span_if_changed(labels, indices, entity):
                repairs.append(LabelRepair(entity.lower(), match.group(0), 0, match.start(), match.end()))

    return repairs


def repair_known_label_issues(
    item: Dict,
) -> Tuple[List[str], List[str], List[LabelRepair]]:
    """
    Repair known weak-label issues.

    The repair is intentionally conservative:
    - sequel markers must be immediately before an episode/special context;
    - sequel marker spans must currently be part of TITLE/O, not group/meta;
    - rows that already have a season before the marker are left alone;
    - structural meta repairs only touch spans after the first episode.
    """
    source_tokens = [str(token) for token in item.get("tokens", [])]
    source_labels = [str(label) for label in item.get("labels", [])]
    if len(source_tokens) != len(source_labels):
        return source_tokens, source_labels, []

    filename = str(item.get("filename") or "")
    text = filename if filename else "".join(source_tokens)
    offsets = token_offsets_in_text(text, source_tokens)
    if offsets is None:
        text = "".join(source_tokens)
        offsets = token_offsets_in_text(text, source_tokens)
    if offsets is None:
        return source_tokens, source_labels, []

    repaired_labels = list(source_labels)
    applied: List[LabelRepair] = []

    quick_text = text.lower()
    has_sequel_marker_hint = any(
        needle in text or needle in quick_text
        for needle in (
            " II", " III", " IV", " V", " VI", " VII", " VIII", " IX",
            "Ⅱ", "Ⅲ", "Ⅳ", "Ⅴ", "Ⅵ", "Ⅶ", "Ⅷ", "Ⅸ",
            "之章", "之期", "之季", "之部", "ノ章", "ノ期", "の章", "の期",
            "貳", "贰", "弐", "弍", "參", "叁", "参", "肆", "陸", "陆",
            "Ni ", " ni ", " no Sara", "Gakki",
        )
    )
    if has_sequel_marker_hint:
        for repair in find_sequel_season_markers(text):
            if labels_have_season_before(repaired_labels, offsets, repair.start):
                continue
            indices = token_indices_for_span(offsets, repair.start, repair.end)
            if not indices:
                continue
            existing = [repaired_labels[idx] for idx in indices]
            if any(
                label.endswith(("GROUP", "EPISODE", "RESOLUTION", "SOURCE", "SPECIAL"))
                for label in existing
            ):
                continue
            if not any(label.endswith("TITLE") for label in existing):
                continue

            label_span(repaired_labels, indices, "SEASON")
            mark_adjacent_title_separators_o(source_tokens, repaired_labels, indices)
            applied.append(repair)

    applied.extend(repair_structural_meta_labels(text, source_tokens, repaired_labels, offsets))
    return source_tokens, repaired_labels, applied


def repair_sequel_season_labels(
    item: Dict,
) -> Tuple[List[str], List[str], List[LabelRepair]]:
    """Backward-compatible wrapper for callers that repair known label issues."""
    return repair_known_label_issues(item)


def repair_jsonl_item(item: Dict) -> Tuple[Dict, List[LabelRepair]]:
    tokens, labels, repairs = repair_known_label_issues(item)
    labels = normalize_iob2(labels)
    if not repairs:
        if labels == item.get("labels", []):
            return item, []
        repaired = dict(item)
        repaired["labels"] = labels
        return repaired, []
    repaired = dict(item)
    repaired["tokens"] = tokens
    repaired["labels"] = labels
    return repaired, repairs


def normalize_iob2(labels: Sequence[str]) -> List[str]:
    normalized: List[str] = []
    previous_entity: Optional[str] = None
    for label in labels:
        if not label.startswith(("B-", "I-")):
            normalized.append("O")
            previous_entity = None
            continue
        entity = label.split("-", 1)[1]
        prefix = "I" if previous_entity == entity else "B"
        normalized.append(f"{prefix}-{entity}")
        previous_entity = entity
    return normalized