File size: 34,440 Bytes
7527970 5cbe47d 7527970 5cbe47d 7527970 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 | from __future__ import annotations
# ruff: noqa: E402
import argparse
import csv
import re
import sys
from pathlib import Path
from typing import Dict, Optional
try:
from scripts.defextra_markers import (
ANCHOR_WINDOW,
ANCHOR_WINDOW_ALT,
DocIndex,
HASH_VERSION,
TokenIndex,
build_tei_index,
hash_token_sequence,
tokenize_text,
normalize_paper_id,
)
except ModuleNotFoundError as exc:
if exc.name != "scripts":
raise
PROJECT_ROOT = Path(__file__).resolve().parent.parent
if str(PROJECT_ROOT) not in sys.path:
sys.path.insert(0, str(PROJECT_ROOT))
from scripts.defextra_markers import (
ANCHOR_WINDOW,
ANCHOR_WINDOW_ALT,
DocIndex,
HASH_VERSION,
TokenIndex,
build_tei_index,
hash_token_sequence,
tokenize_text,
normalize_paper_id,
)
TRAILING_PUNCT = {".", ",", ";", ":", "?", "!"}
TRAILING_QUOTES = {"'", '"', "”", "’", ")", "]"}
CITATION_BRACKET_RE = re.compile(r"\[[0-9][0-9,;\s\-–]*\]")
CITATION_PAREN_RE = re.compile(r"\([^)]*\d{4}[^)]*\)")
def _extract_end_punct(text: str) -> str:
trimmed = text.rstrip()
if not trimmed:
return ""
i = len(trimmed) - 1
while i >= 0 and trimmed[i] in TRAILING_QUOTES:
i -= 1
if i >= 0 and trimmed[i] in TRAILING_PUNCT:
return trimmed[i]
return ""
def _spec(
count: str,
hash64: str,
sha: str,
) -> Optional[tuple[int, int, str]]:
if not count or not hash64 or not sha:
return None
try:
return int(count), int(hash64), sha
except ValueError:
return None
def _build_mid_candidates(
token_index: TokenIndex,
mid_specs: list[tuple[int, int, str]],
) -> list[tuple[int, int]]:
if not mid_specs:
return []
candidates: list[tuple[int, int]] = []
for spec in mid_specs:
for position in token_index.find_token_positions_by_hash(*spec):
candidates.append((position, spec[0]))
return candidates
def _span_has_mid(
mid_candidates: list[tuple[int, int]],
start_idx: int,
end_idx: int,
) -> bool:
for mid_start, mid_len in mid_candidates:
mid_end = mid_start + mid_len - 1
if mid_start >= start_idx and mid_end <= end_idx:
return True
return False
def _find_span_by_anchors(
token_index: TokenIndex,
head_spec: Optional[tuple[int, int, str]],
tail_spec: Optional[tuple[int, int, str]],
expected_len: int,
mid_specs: Optional[list[tuple[int, int, str]]] = None,
) -> Optional[tuple[int, int]]:
if head_spec is None or tail_spec is None or expected_len <= 0:
return None
head_positions = token_index.find_token_positions_by_hash(*head_spec)
tail_positions = token_index.find_token_positions_by_hash(*tail_spec)
if not head_positions or not tail_positions:
return None
mid_candidates = _build_mid_candidates(token_index, mid_specs or [])
best = None
best_diff = None
tol = max(5, int(expected_len * 0.3))
min_len = max(1, expected_len // 2)
max_len = expected_len * 3
for head_start in head_positions:
head_end = head_start + head_spec[0] - 1
for tail_start in tail_positions:
tail_end = tail_start + tail_spec[0] - 1
if tail_end < head_end:
continue
if mid_candidates and not _span_has_mid(
mid_candidates,
head_start,
tail_end,
):
continue
length = tail_end - head_start + 1
if length < min_len or length > max_len:
continue
if length < expected_len - tol or length > expected_len + tol:
continue
diff = abs(length - expected_len)
if best_diff is None or diff < best_diff:
best_diff = diff
best = (head_start, tail_end)
if best is None:
return None
start_char = token_index.spans[best[0]][0]
end_char = token_index.spans[best[1]][1]
return start_char, end_char
def _find_span_from_anchor(
token_index: TokenIndex,
anchor_spec: Optional[tuple[int, int, str]],
expected_len: int,
position: str,
mid_specs: Optional[list[tuple[int, int, str]]] = None,
) -> Optional[tuple[int, int]]:
if anchor_spec is None or expected_len <= 0:
return None
positions = token_index.find_token_positions_by_hash(*anchor_spec)
if not positions:
return None
mid_candidates = _build_mid_candidates(token_index, mid_specs or [])
if position == "tail":
positions = list(reversed(positions))
for anchor_start in positions:
if position == "head":
start_idx = anchor_start
end_idx = anchor_start + expected_len - 1
else:
anchor_end = anchor_start + anchor_spec[0] - 1
end_idx = anchor_end
start_idx = end_idx - expected_len + 1
if start_idx < 0 or end_idx >= len(token_index.tokens):
continue
if mid_candidates and not _span_has_mid(
mid_candidates,
start_idx,
end_idx,
):
continue
start_char = token_index.spans[start_idx][0]
end_char = token_index.spans[end_idx][1]
return start_char, end_char
return None
def _candidate_ids(paper_id: str, doi: str, arxiv: str) -> list[str]:
candidates = [paper_id, normalize_paper_id(paper_id)]
if doi:
candidates.append(doi)
if arxiv:
candidates.append(arxiv)
seen = set()
ordered = []
for item in candidates:
value = item.strip()
if value and value not in seen:
seen.add(value)
ordered.append(value)
return ordered
def _resolve_tei_path(
paper_id: str,
doi: str,
arxiv: str,
tei_index: Dict[str, Path],
) -> Optional[Path]:
for candidate in _candidate_ids(paper_id, doi, arxiv):
if candidate in tei_index:
return tei_index[candidate]
if candidate.startswith("paper_"):
stripped = candidate[len("paper_") :]
if stripped in tei_index:
return tei_index[stripped]
return None
def main() -> None:
parser = argparse.ArgumentParser(
description="Build legal DefExtra CSV with GROBID markers.",
)
parser.add_argument(
"--input-csv",
type=Path,
default=Path("results/paper_results/defextra_hf.csv"),
help="Source DefExtra CSV (contains excerpts).",
)
parser.add_argument(
"--output-csv",
type=Path,
default=Path("results/paper_results/defextra_legal.csv"),
help="Output legal DefExtra CSV (no excerpts).",
)
parser.add_argument(
"--tei-dir",
type=Path,
nargs="+",
default=[
Path("ManualPDFsGROBID/manual_pdfs_grobid"),
Path("ManualPDFsGROBID/new_grobid"),
],
help="Directories with GROBID TEI files.",
)
parser.add_argument(
"--report",
type=Path,
default=None,
help="Optional report path for missing TEI spans.",
)
args = parser.parse_args()
if not args.input_csv.exists():
raise SystemExit(f"Input CSV not found: {args.input_csv}")
tei_index = build_tei_index(args.tei_dir)
doc_cache: Dict[str, Optional[DocIndex]] = {}
token_cache: Dict[str, Optional[TokenIndex]] = {}
rows = []
with args.input_csv.open("r", encoding="utf-8", newline="") as handle:
reader = csv.DictReader(handle)
for row in reader:
rows.append(row)
output_rows = []
missing_tei = 0
missing_def = 0
missing_ctx = 0
missing_def_rows: list[dict] = []
missing_ctx_rows: list[dict] = []
def_hash_available = 0
ctx_hash_available = 0
def_anchor_available = 0
ctx_anchor_available = 0
for row in rows:
paper_id = (row.get("paper_id") or "").strip()
doi = (row.get("paper_doi") or "").strip()
arxiv = (row.get("paper_arxiv") or "").strip()
definition = row.get("definition") or ""
context = row.get("context") or ""
if paper_id not in doc_cache:
tei_path = _resolve_tei_path(paper_id, doi, arxiv, tei_index)
if tei_path is None:
doc_cache[paper_id] = None
token_cache[paper_id] = None
else:
doc_index = DocIndex.from_tei(tei_path)
doc_cache[paper_id] = doc_index
token_cache[paper_id] = TokenIndex.from_text(
doc_index.doc_text,
)
doc_index = doc_cache.get(paper_id)
def_start = def_end = ctx_start = ctx_end = ""
def_match = ctx_match = "missing"
def_hash64 = def_sha = def_tok_len = ""
ctx_hash64 = ctx_sha = ctx_tok_len = ""
def_head_hash64 = def_head_sha = def_head_len = ""
def_tail_hash64 = def_tail_sha = def_tail_len = ""
def_mid_hash64 = def_mid_sha = def_mid_len = ""
def_head_alt_hash64 = def_head_alt_sha = def_head_alt_len = ""
def_tail_alt_hash64 = def_tail_alt_sha = def_tail_alt_len = ""
def_mid_alt_hash64 = def_mid_alt_sha = def_mid_alt_len = ""
ctx_head_hash64 = ctx_head_sha = ctx_head_len = ""
ctx_tail_hash64 = ctx_tail_sha = ctx_tail_len = ""
ctx_mid_hash64 = ctx_mid_sha = ctx_mid_len = ""
ctx_head_alt_hash64 = ctx_head_alt_sha = ctx_head_alt_len = ""
ctx_tail_alt_hash64 = ctx_tail_alt_sha = ctx_tail_alt_len = ""
ctx_mid_alt_hash64 = ctx_mid_alt_sha = ctx_mid_alt_len = ""
def_anchor_has = False
ctx_anchor_has = False
def_preserve_linebreaks = "true" if "\n" in definition else "false"
ctx_preserve_linebreaks = "true" if "\n" in context else "false"
def_preserve_hyphenation = (
"true"
if re.search(r"[A-Za-z]-\s+[A-Za-z]", definition)
else "false"
)
ctx_preserve_hyphenation = (
"true" if re.search(r"[A-Za-z]-\s+[A-Za-z]", context) else "false"
)
def_has_bracket_citation = (
"true" if CITATION_BRACKET_RE.search(definition) else "false"
)
def_has_paren_citation = (
"true" if CITATION_PAREN_RE.search(definition) else "false"
)
def_has_letter_digit = (
"true" if re.search(r"[A-Za-z][0-9]", definition) else "false"
)
ctx_has_bracket_citation = (
"true" if CITATION_BRACKET_RE.search(context) else "false"
)
ctx_has_paren_citation = (
"true" if CITATION_PAREN_RE.search(context) else "false"
)
ctx_has_letter_digit = (
"true" if re.search(r"[A-Za-z][0-9]", context) else "false"
)
def_end_punct = _extract_end_punct(definition)
ctx_end_punct = _extract_end_punct(context)
def_tokens, _ = tokenize_text(definition, return_spans=False)
if def_tokens:
h64, sha, tok_len = hash_token_sequence(def_tokens)
def_hash64 = str(h64)
def_sha = sha
def_tok_len = str(tok_len)
def_hash_available += 1
if tok_len >= ANCHOR_WINDOW:
h64, sha, tok_len = hash_token_sequence(
def_tokens[:ANCHOR_WINDOW],
)
def_head_hash64 = str(h64)
def_head_sha = sha
def_head_len = str(tok_len)
h64, sha, tok_len = hash_token_sequence(
def_tokens[-ANCHOR_WINDOW:],
)
def_tail_hash64 = str(h64)
def_tail_sha = sha
def_tail_len = str(tok_len)
mid_start = max(0, (len(def_tokens) - ANCHOR_WINDOW) // 2)
h64, sha, tok_len = hash_token_sequence(
def_tokens[mid_start : mid_start + ANCHOR_WINDOW],
)
def_mid_hash64 = str(h64)
def_mid_sha = sha
def_mid_len = str(tok_len)
def_anchor_has = True
if tok_len >= 2:
alt_window = (
ANCHOR_WINDOW_ALT
if tok_len >= ANCHOR_WINDOW_ALT
else max(2, tok_len - 1)
)
h64, sha, tok_len = hash_token_sequence(
def_tokens[:alt_window],
)
def_head_alt_hash64 = str(h64)
def_head_alt_sha = sha
def_head_alt_len = str(tok_len)
h64, sha, tok_len = hash_token_sequence(
def_tokens[-alt_window:],
)
def_tail_alt_hash64 = str(h64)
def_tail_alt_sha = sha
def_tail_alt_len = str(tok_len)
mid_start = max(0, (len(def_tokens) - alt_window) // 2)
h64, sha, tok_len = hash_token_sequence(
def_tokens[mid_start : mid_start + alt_window],
)
def_mid_alt_hash64 = str(h64)
def_mid_alt_sha = sha
def_mid_alt_len = str(tok_len)
def_anchor_has = True
ctx_tokens, _ = tokenize_text(context, return_spans=False)
if ctx_tokens:
h64, sha, tok_len = hash_token_sequence(ctx_tokens)
ctx_hash64 = str(h64)
ctx_sha = sha
ctx_tok_len = str(tok_len)
ctx_hash_available += 1
if tok_len >= ANCHOR_WINDOW:
h64, sha, tok_len = hash_token_sequence(
ctx_tokens[:ANCHOR_WINDOW],
)
ctx_head_hash64 = str(h64)
ctx_head_sha = sha
ctx_head_len = str(tok_len)
h64, sha, tok_len = hash_token_sequence(
ctx_tokens[-ANCHOR_WINDOW:],
)
ctx_tail_hash64 = str(h64)
ctx_tail_sha = sha
ctx_tail_len = str(tok_len)
mid_start = max(0, (len(ctx_tokens) - ANCHOR_WINDOW) // 2)
h64, sha, tok_len = hash_token_sequence(
ctx_tokens[mid_start : mid_start + ANCHOR_WINDOW],
)
ctx_mid_hash64 = str(h64)
ctx_mid_sha = sha
ctx_mid_len = str(tok_len)
ctx_anchor_has = True
if tok_len >= 2:
alt_window = (
ANCHOR_WINDOW_ALT
if tok_len >= ANCHOR_WINDOW_ALT
else max(2, tok_len - 1)
)
h64, sha, tok_len = hash_token_sequence(
ctx_tokens[:alt_window],
)
ctx_head_alt_hash64 = str(h64)
ctx_head_alt_sha = sha
ctx_head_alt_len = str(tok_len)
h64, sha, tok_len = hash_token_sequence(
ctx_tokens[-alt_window:],
)
ctx_tail_alt_hash64 = str(h64)
ctx_tail_alt_sha = sha
ctx_tail_alt_len = str(tok_len)
mid_start = max(0, (len(ctx_tokens) - alt_window) // 2)
h64, sha, tok_len = hash_token_sequence(
ctx_tokens[mid_start : mid_start + alt_window],
)
ctx_mid_alt_hash64 = str(h64)
ctx_mid_alt_sha = sha
ctx_mid_alt_len = str(tok_len)
ctx_anchor_has = True
if def_anchor_has:
def_anchor_available += 1
if ctx_anchor_has:
ctx_anchor_available += 1
def_head_spec = _spec(def_head_len, def_head_hash64, def_head_sha)
def_head_alt_spec = _spec(
def_head_alt_len,
def_head_alt_hash64,
def_head_alt_sha,
)
def_mid_spec = _spec(def_mid_len, def_mid_hash64, def_mid_sha)
def_mid_alt_spec = _spec(
def_mid_alt_len,
def_mid_alt_hash64,
def_mid_alt_sha,
)
def_tail_spec = _spec(def_tail_len, def_tail_hash64, def_tail_sha)
def_tail_alt_spec = _spec(
def_tail_alt_len,
def_tail_alt_hash64,
def_tail_alt_sha,
)
ctx_head_spec = _spec(ctx_head_len, ctx_head_hash64, ctx_head_sha)
ctx_head_alt_spec = _spec(
ctx_head_alt_len,
ctx_head_alt_hash64,
ctx_head_alt_sha,
)
ctx_mid_spec = _spec(ctx_mid_len, ctx_mid_hash64, ctx_mid_sha)
ctx_mid_alt_spec = _spec(
ctx_mid_alt_len,
ctx_mid_alt_hash64,
ctx_mid_alt_sha,
)
ctx_tail_spec = _spec(ctx_tail_len, ctx_tail_hash64, ctx_tail_sha)
ctx_tail_alt_spec = _spec(
ctx_tail_alt_len,
ctx_tail_alt_hash64,
ctx_tail_alt_sha,
)
token_index = token_cache.get(paper_id)
if doc_index is None:
missing_tei += 1
else:
def_span = doc_index.find_span(definition)
if def_span is not None:
def_start, def_end, def_match = def_span
else:
if def_hash64 and def_sha and def_tok_len and token_index:
span = token_index.find_span_by_hash(
int(def_tok_len),
int(def_hash64),
def_sha,
)
if span:
def_start, def_end = span
def_match = "hash"
else:
expected_len = int(def_tok_len or 0)
head_specs = [
spec
for spec in (def_head_spec, def_head_alt_spec)
if spec
]
mid_specs = [
spec
for spec in (def_mid_spec, def_mid_alt_spec)
if spec
]
tail_specs = [
spec
for spec in (def_tail_spec, def_tail_alt_spec)
if spec
]
if (
token_index
and expected_len
and head_specs
and tail_specs
):
for head in head_specs:
for tail in tail_specs:
anchor_span = _find_span_by_anchors(
token_index,
head,
tail,
expected_len,
mid_specs=mid_specs,
)
if anchor_span:
def_start, def_end = anchor_span
def_match = "anchor"
break
if def_match == "anchor":
break
if (
def_match != "anchor"
and token_index
and expected_len
):
for spec, position in (
(def_head_spec, "head"),
(def_head_alt_spec, "head"),
(def_mid_spec, "head"),
(def_mid_alt_spec, "head"),
(def_tail_spec, "tail"),
(def_tail_alt_spec, "tail"),
):
anchor_span = _find_span_from_anchor(
token_index,
spec,
expected_len,
position,
mid_specs=mid_specs,
)
if anchor_span:
def_start, def_end = anchor_span
def_match = "anchor"
break
if def_match != "anchor":
missing_def += 1
missing_def_rows.append(
{
"paper_id": paper_id,
"concept": row.get("concept", ""),
"reason": "missing_definition_span",
},
)
else:
missing_def += 1
missing_def_rows.append(
{
"paper_id": paper_id,
"concept": row.get("concept", ""),
"reason": "missing_definition_span",
},
)
ctx_span = doc_index.find_span(context)
if ctx_span is not None:
ctx_start, ctx_end, ctx_match = ctx_span
else:
if ctx_hash64 and ctx_sha and ctx_tok_len and token_index:
span = token_index.find_span_by_hash(
int(ctx_tok_len),
int(ctx_hash64),
ctx_sha,
)
if span:
ctx_start, ctx_end = span
ctx_match = "hash"
else:
expected_len = int(ctx_tok_len or 0)
head_specs = [
spec
for spec in (ctx_head_spec, ctx_head_alt_spec)
if spec
]
mid_specs = [
spec
for spec in (ctx_mid_spec, ctx_mid_alt_spec)
if spec
]
tail_specs = [
spec
for spec in (ctx_tail_spec, ctx_tail_alt_spec)
if spec
]
if (
token_index
and expected_len
and head_specs
and tail_specs
):
for head in head_specs:
for tail in tail_specs:
anchor_span = _find_span_by_anchors(
token_index,
head,
tail,
expected_len,
mid_specs=mid_specs,
)
if anchor_span:
ctx_start, ctx_end = anchor_span
ctx_match = "anchor"
break
if ctx_match == "anchor":
break
if (
ctx_match != "anchor"
and token_index
and expected_len
):
for spec, position in (
(ctx_head_spec, "head"),
(ctx_head_alt_spec, "head"),
(ctx_mid_spec, "head"),
(ctx_mid_alt_spec, "head"),
(ctx_tail_spec, "tail"),
(ctx_tail_alt_spec, "tail"),
):
anchor_span = _find_span_from_anchor(
token_index,
spec,
expected_len,
position,
mid_specs=mid_specs,
)
if anchor_span:
ctx_start, ctx_end = anchor_span
ctx_match = "anchor"
break
if ctx_match != "anchor":
missing_ctx += 1
missing_ctx_rows.append(
{
"paper_id": paper_id,
"concept": row.get("concept", ""),
"reason": "missing_context_span",
},
)
else:
missing_ctx += 1
missing_ctx_rows.append(
{
"paper_id": paper_id,
"concept": row.get("concept", ""),
"reason": "missing_context_span",
},
)
output_rows.append(
{
"paper_id": paper_id,
"paper_title": row.get("paper_title", ""),
"paper_doi": doi,
"paper_arxiv": arxiv,
"concept": row.get("concept", ""),
"definition_type": row.get("definition_type", ""),
"source_file": row.get("source_file", ""),
"is_out_of_domain": row.get("is_out_of_domain", ""),
"definition_preserve_linebreaks": def_preserve_linebreaks,
"context_preserve_linebreaks": ctx_preserve_linebreaks,
"definition_preserve_hyphenation": def_preserve_hyphenation,
"context_preserve_hyphenation": ctx_preserve_hyphenation,
"definition_has_bracket_citation": def_has_bracket_citation,
"definition_has_paren_citation": def_has_paren_citation,
"definition_has_letter_digit": def_has_letter_digit,
"context_has_bracket_citation": ctx_has_bracket_citation,
"context_has_paren_citation": ctx_has_paren_citation,
"context_has_letter_digit": ctx_has_letter_digit,
"definition_end_punct": def_end_punct,
"context_end_punct": ctx_end_punct,
"marker_version": "grobid_text_v1",
"hash_version": HASH_VERSION,
"definition_char_start": def_start,
"definition_char_end": def_end,
"definition_match": def_match,
"definition_hash64": def_hash64,
"definition_sha256": def_sha,
"definition_token_count": def_tok_len,
"definition_head_hash64": def_head_hash64,
"definition_head_sha256": def_head_sha,
"definition_head_token_count": def_head_len,
"definition_mid_hash64": def_mid_hash64,
"definition_mid_sha256": def_mid_sha,
"definition_mid_token_count": def_mid_len,
"definition_tail_hash64": def_tail_hash64,
"definition_tail_sha256": def_tail_sha,
"definition_tail_token_count": def_tail_len,
"definition_head_alt_hash64": def_head_alt_hash64,
"definition_head_alt_sha256": def_head_alt_sha,
"definition_head_alt_token_count": def_head_alt_len,
"definition_mid_alt_hash64": def_mid_alt_hash64,
"definition_mid_alt_sha256": def_mid_alt_sha,
"definition_mid_alt_token_count": def_mid_alt_len,
"definition_tail_alt_hash64": def_tail_alt_hash64,
"definition_tail_alt_sha256": def_tail_alt_sha,
"definition_tail_alt_token_count": def_tail_alt_len,
"context_char_start": ctx_start,
"context_char_end": ctx_end,
"context_match": ctx_match,
"context_hash64": ctx_hash64,
"context_sha256": ctx_sha,
"context_token_count": ctx_tok_len,
"context_head_hash64": ctx_head_hash64,
"context_head_sha256": ctx_head_sha,
"context_head_token_count": ctx_head_len,
"context_mid_hash64": ctx_mid_hash64,
"context_mid_sha256": ctx_mid_sha,
"context_mid_token_count": ctx_mid_len,
"context_tail_hash64": ctx_tail_hash64,
"context_tail_sha256": ctx_tail_sha,
"context_tail_token_count": ctx_tail_len,
"context_head_alt_hash64": ctx_head_alt_hash64,
"context_head_alt_sha256": ctx_head_alt_sha,
"context_head_alt_token_count": ctx_head_alt_len,
"context_mid_alt_hash64": ctx_mid_alt_hash64,
"context_mid_alt_sha256": ctx_mid_alt_sha,
"context_mid_alt_token_count": ctx_mid_alt_len,
"context_tail_alt_hash64": ctx_tail_alt_hash64,
"context_tail_alt_sha256": ctx_tail_alt_sha,
"context_tail_alt_token_count": ctx_tail_alt_len,
},
)
fieldnames = [
"paper_id",
"paper_title",
"paper_doi",
"paper_arxiv",
"concept",
"definition_type",
"source_file",
"is_out_of_domain",
"definition_preserve_linebreaks",
"context_preserve_linebreaks",
"definition_preserve_hyphenation",
"context_preserve_hyphenation",
"definition_has_bracket_citation",
"definition_has_paren_citation",
"definition_has_letter_digit",
"context_has_bracket_citation",
"context_has_paren_citation",
"context_has_letter_digit",
"definition_end_punct",
"context_end_punct",
"marker_version",
"hash_version",
"definition_char_start",
"definition_char_end",
"definition_match",
"definition_hash64",
"definition_sha256",
"definition_token_count",
"definition_head_hash64",
"definition_head_sha256",
"definition_head_token_count",
"definition_mid_hash64",
"definition_mid_sha256",
"definition_mid_token_count",
"definition_tail_hash64",
"definition_tail_sha256",
"definition_tail_token_count",
"definition_head_alt_hash64",
"definition_head_alt_sha256",
"definition_head_alt_token_count",
"definition_mid_alt_hash64",
"definition_mid_alt_sha256",
"definition_mid_alt_token_count",
"definition_tail_alt_hash64",
"definition_tail_alt_sha256",
"definition_tail_alt_token_count",
"context_char_start",
"context_char_end",
"context_match",
"context_hash64",
"context_sha256",
"context_token_count",
"context_head_hash64",
"context_head_sha256",
"context_head_token_count",
"context_mid_hash64",
"context_mid_sha256",
"context_mid_token_count",
"context_tail_hash64",
"context_tail_sha256",
"context_tail_token_count",
"context_head_alt_hash64",
"context_head_alt_sha256",
"context_head_alt_token_count",
"context_mid_alt_hash64",
"context_mid_alt_sha256",
"context_mid_alt_token_count",
"context_tail_alt_hash64",
"context_tail_alt_sha256",
"context_tail_alt_token_count",
]
args.output_csv.parent.mkdir(parents=True, exist_ok=True)
with args.output_csv.open("w", encoding="utf-8", newline="") as handle:
writer = csv.DictWriter(handle, fieldnames=fieldnames)
writer.writeheader()
for row in output_rows:
writer.writerow(row)
total = len(output_rows)
print(f"Wrote {total} rows to {args.output_csv}")
print(
"Exact TEI spans missing - "
f"TEI: {missing_tei}, def spans: {missing_def}, ctx spans: {missing_ctx}",
)
print(
"Hash/anchor markers available - "
f"def hash: {def_hash_available}/{total}, "
f"ctx hash: {ctx_hash_available}/{total}, "
f"def anchors: {def_anchor_available}/{total}, "
f"ctx anchors: {ctx_anchor_available}/{total}",
)
print(
"Note: missing exact TEI spans do not block hydration; "
"hash/anchor markers are used as the primary fallback.",
)
if args.report is not None:
report_lines = []
if missing_tei:
report_lines.append(f"Missing TEI: {missing_tei}")
report_lines.append(f"Missing definition spans: {missing_def}")
report_lines.append(f"Missing context spans: {missing_ctx}")
if missing_def_rows:
report_lines.append("")
report_lines.append("Missing definitions (paper_id | concept):")
for item in missing_def_rows:
report_lines.append(
f"- {item['paper_id']} | {item['concept']}",
)
if missing_ctx_rows:
report_lines.append("")
report_lines.append("Missing contexts (paper_id | concept):")
for item in missing_ctx_rows:
report_lines.append(
f"- {item['paper_id']} | {item['concept']}",
)
args.report.parent.mkdir(parents=True, exist_ok=True)
args.report.write_text(
"\n".join(report_lines) + "\n",
encoding="utf-8",
)
print(f"Wrote report to {args.report}")
if __name__ == "__main__":
main()
|