#!/usr/bin/env python """Assemble the LLM annotations into a drop-in replacement for corpus/perdt-ner-iob. python scripts/annotation/export_iob.py Writes two-column IOB2 (`token\\tTAG`, blank line between sentences) in the exact sentence order and tokenization of the source corpus, so the result can be swapped into project.yml's `spacy convert` step by changing one path: corpus/perdt-ner-iob-llm/{train,dev,test}.txt Sentence order and token strings are asserted against corpus/perdt-ner-iob, so a partial or misaligned annotation set fails loudly instead of silently training on shifted labels. The output lives under corpus/ because it is a build artifact regenerable from the committed JSONL in annotation/data/llm/. """ import argparse import json from pathlib import Path SOURCES = { "train": [f"train/shard-{i:03d}" for i in range(14)], "dev": ["dev-all"], "test": ["test-all"], } def iob_sents(path): sents, cur = [], [] for line in path.open(encoding="utf8"): line = line.rstrip("\n") if not line.strip(): if cur: sents.append(cur) cur = [] continue parts = line.split("\t") if "\t" in line else line.split() cur.append(parts[0]) if cur: sents.append(cur) return sents def tag(tokens, entities): tags = ["O"] * len(tokens) for e in entities: tags[e["start"]] = f"B-{e['label']}" for i in range(e["start"] + 1, e["end"]): tags[i] = f"I-{e['label']}" return tags def main(): ap = argparse.ArgumentParser(description=__doc__) ap.add_argument("--llm-dir", default="annotation/data/llm/ner-v2.2-default") ap.add_argument("--reference", default="corpus/perdt-ner-iob") ap.add_argument("--out-dir", default="corpus/perdt-ner-iob-llm") args = ap.parse_args() out_dir = Path(args.out_dir) out_dir.mkdir(parents=True, exist_ok=True) for split, parts in SOURCES.items(): rows = [] for part in parts: path = Path(args.llm_dir) / f"{part}.jsonl" rows += [json.loads(line) for line in path.open(encoding="utf8")] ref = iob_sents(Path(args.reference) / f"{split}.txt") if len(rows) != len(ref): raise SystemExit(f"{split}: {len(rows)} annotated sentences against {len(ref)} in corpus") for i, (row, tokens) in enumerate(zip(rows, ref)): if row["tokens"] != tokens: raise SystemExit(f"{split}: token mismatch at sentence {i} ({row['id']})") blocks, spans, unannotated = [], 0, 0 for row in rows: spans += len(row["entities"]) unannotated += 1 if row.get("error") == "missing" else 0 tags = tag(row["tokens"], row["entities"]) blocks.append("\n".join(f"{t}\t{g}" for t, g in zip(row["tokens"], tags))) # trailing blank line, matching corpus/perdt-ner-iob byte for byte in column 1 (out_dir / f"{split}.txt").write_text("\n\n".join(blocks) + "\n\n", encoding="utf8") print(f"{split}.txt: {len(rows)} sentences, {spans} entities, " f"{unannotated} unannotated -> {out_dir / f'{split}.txt'}") if __name__ == "__main__": main()