| """Citation-level labels from LePhantomCite (ai-law-society-lab/Legal_Phantom_Citation). | |
| phantom = citation tagged non_existent_citation | |
| genuine = citation with no hallucination tag at all | |
| other = tagged case_name_mismatch / wrong_pincite / misquote / content_misrepresentation | |
| (needs a case-law lookup; out of scope for a string-only model, reported separately) | |
| 'optional' tags (typos in the source brief) are dropped. | |
| """ | |
| import json, os, sys | |
| sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) | |
| from citenet.text import normalize | |
| ROOT = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "data") | |
| def load(split): | |
| rows = [json.loads(l) for l in open(os.path.join(ROOT, split + ".jsonl"))] | |
| out = [] | |
| for r in rows: | |
| tags = r.get("list_hallucination_types") or {} | |
| opt = {k for k, v in (r.get("list_hallucinations") or {}).items() if v == "optional"} | |
| cites = list(dict.fromkeys(list(r["citations_in_segment"]) + list(tags))) | |
| seen = set() | |
| for c in cites: | |
| key = normalize(c) | |
| if key in seen or c in opt: | |
| continue | |
| seen.add(key) | |
| ts = tags.get(c, []) | |
| if "optional" in ts: | |
| continue | |
| label = "phantom" if "non_existent_citation" in ts else ("other" if ts else "genuine") | |
| out.append(dict(cite=c, label=label, types=ts, file=r["filename"])) | |
| return out | |