| |
| """Agreement between the published labels and a second annotator's: Cohen's kappa, |
| raw agreement, and the confusion of the disagreements. |
| |
| python3 scripts/kappa.py annotation/round-2/sample.csv |
| """ |
| import csv |
| import sys |
| from collections import Counter |
|
|
| from common import ROLES, data, read_jsonl |
|
|
| if len(sys.argv) != 2: |
| sys.exit(__doc__) |
| first = {l["id"]: l["role"] for l in read_jsonl(data("roles", "labels.jsonl"))} |
| rows = [r for r in csv.DictReader(open(sys.argv[1], encoding="utf-8")) if r["role"].strip()] |
| bad = [r["id"] for r in rows if r["role"].strip() not in ROLES or r["id"] not in first] |
| if bad: |
| sys.exit(f"unknown role or id: {', '.join(bad[:10])}") |
| pairs = [(first[r["id"]], r["role"].strip()) for r in rows] |
| n = len(pairs) |
| if not n: |
| sys.exit("no row has a role yet") |
| po = sum(a == b for a, b in pairs) / n |
| ca, cb = Counter(a for a, _ in pairs), Counter(b for _, b in pairs) |
| pe = sum(ca[r] * cb[r] for r in ROLES) / (n * n) |
| kappa = (po - pe) / (1 - pe) if pe < 1 else 1.0 |
| print(f"{n} labels compared · agreement {100 * po:.1f} % · Cohen's kappa {kappa:.3f}") |
| for (a, b), k in Counter((a, b) for a, b in pairs if a != b).most_common(): |
| print(f" round 1 {a:<12} round 2 {b:<12} {k}") |
|
|
