| from __future__ import annotations |
|
|
| import argparse |
| from pathlib import Path |
| from typing import Any |
|
|
| from src.data.io_utils import read_jsonl |
|
|
|
|
| def compact(text: Any, limit: int = 240) -> str: |
| value = " ".join(str(text or "").split()) |
| if len(value) <= limit: |
| return value |
| clipped = value[:limit].rsplit(" ", 1)[0].strip() |
| return f"{clipped}..." |
|
|
|
|
| def render_prediction_case(row: dict[str, Any]) -> list[str]: |
| lines = [ |
| f"### {row.get('category', '')}: {row.get('id', '')}", |
| f"- Claim: {row.get('claim', '')}", |
| f"- Gold / baseline / WikiKG / alternate: `{row.get('gold', '')}` / `{row.get('baseline_prediction', '')}` / `{row.get('wikikg_prediction', '')}` / `{row.get('alternate_prediction', '')}`", |
| f"- Verified support: `{row.get('num_verified_facts', 0)}` facts, `{row.get('num_verified_triples', 0)}` triples", |
| ] |
| path_summary = row.get("path_summary", {}) |
| if path_summary: |
| lines.append( |
| "- Path summary: " |
| f"max_final={path_summary.get('max_final_score', '')}, " |
| f"max_kg_path={path_summary.get('max_kg_path_score', '')}, " |
| f"max_provenance={path_summary.get('max_provenance_confidence', '')}" |
| ) |
| if row.get("top_evidence"): |
| lines.append("- Top evidence:") |
| for item in row["top_evidence"][:3]: |
| lines.append(f" - [{item.get('candidate_id', '')}] {compact(item.get('text', ''))}") |
| if row.get("top_verified_paths"): |
| lines.append("- Top verified paths:") |
| for item in row["top_verified_paths"][:3]: |
| lines.append(f" - {item.get('path_text', '')}") |
| lines.append(f" - Source: {compact(item.get('source_text', ''))}") |
| if row.get("top_unsupported_triples"): |
| lines.append("- Unsupported triples:") |
| for item in row["top_unsupported_triples"][:2]: |
| lines.append(f" - {item.get('path_text', '')} [{item.get('nli_label', '')}]") |
| lines.append("") |
| return lines |
|
|
|
|
| def render_relation_case(row: dict[str, Any]) -> list[str]: |
| lines = [ |
| f"### {row.get('category', '')}: {row.get('id', '')}", |
| f"- Claim: {row.get('claim', '')}", |
| f"- Gold / baseline / WikiKG: `{row.get('gold', '')}` / `{row.get('baseline_prediction', '')}` / `{row.get('wikikg_prediction', '')}`", |
| f"- Relation: `{row.get('relation_original', '') or row.get('relation', '')}` -> `{row.get('relation', '')}`", |
| f"- NLI / entailment: `{row.get('nli_label', '')}` / `{row.get('entailment_score', '')}`", |
| f"- Triple: {row.get('verbalized_triple', '')}", |
| f"- Source: {compact(row.get('source_text', ''), limit=320)}", |
| "", |
| ] |
| return lines |
|
|
|
|
| def render_section(title: str, rows: list[dict[str, Any]], relation_mode: bool = False) -> list[str]: |
| lines = [f"## {title}", ""] |
| if not rows: |
| lines.append("No cases selected.") |
| lines.append("") |
| return lines |
| current_category = None |
| for row in rows: |
| if row.get("category") != current_category: |
| current_category = row.get("category") |
| lines.append(f"### Group: {current_category}") |
| lines.append("") |
| lines.extend(render_relation_case(row) if relation_mode else render_prediction_case(row)) |
| return lines |
|
|
|
|
| def main() -> None: |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--averitec", type=Path, required=True) |
| parser.add_argument("--healthver", type=Path, required=True) |
| parser.add_argument("--vifactcheck", type=Path, required=True) |
| parser.add_argument("--output", type=Path, default=Path("outputs/analysis/case_studies.md")) |
| args = parser.parse_args() |
|
|
| averitec_rows = read_jsonl(args.averitec) |
| healthver_rows = read_jsonl(args.healthver) |
| vifactcheck_rows = read_jsonl(args.vifactcheck) |
|
|
| lines = ["# Stage 11 Case Studies", ""] |
| lines.extend(render_section("AVeriTeC", averitec_rows)) |
| lines.extend(render_section("HealthVer", healthver_rows, relation_mode=True)) |
| lines.extend(render_section("ViFactCheck", vifactcheck_rows)) |
| args.output.parent.mkdir(parents=True, exist_ok=True) |
| args.output.write_text("\n".join(lines).strip() + "\n", encoding="utf-8") |
| print(f"Wrote case studies to {args.output}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
