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Datasets:
alizahidraja
/
isnad-bench

Tasks:
Text Classification
Languages:
Arabic
ArXiv:
Tags:
hadith
isnad
provenance
trust
chain-grading
benchmark
License:
Dataset card Files
xet
 Community
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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 0
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
                  df = pandas_read_json(f)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                         ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
                  obj = self._get_object_parser(self.data)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
                  self._parse()
                  ~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
                  ujson_loads(json, precise_float=self.precise_float), dtype=None
                  ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4408, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2679, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2861, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2395, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 327, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                  return check_status(status)
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0

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ISNAD-Bench — derived graded output

One reproducible agreement number between ISNAD's weakest-link chain grading and 1,200 years of labelled hadith ground truth.

What this is (and is not)

This is derived output, not a re-host of the source data. The underlying dataset is emadjumaah/hadith-kg (CC-BY-4.0). This dataset contains, per chain, the scholar's verdict, ISNAD's predicted chain grade, and the principled disagreement bucket — computed by the exact functions that produce the benchmark's κ.

The headline number — and how to read it

ISNAD's weakest-link chain grading reproduces 1,200 years of classical hadith scholars' chain verdicts at Cohen's κ = 0.871 (strict default), across 577,024 scholar-graded chains, with a shuffled-rank control at κ = 0.047.

ISNAD faithfully implements the scholars' consensus; it is not "better than the scholars". The human ceiling — how well the scholars agree with each other — is κ = 0.331 (critic-vs-critic). ISNAD's 0.871 means it is a deterministic reflection of the scholars' average opinion, on a scale where they disagree with each other at 0.331. The consensus it tracks is the honest upper bound, not a thing to exceed.

Leaderboard

Model / method κ (strict) Human ceiling Source
ISNAD weakest-link (strict) 0.871 0.331 this dataset · bench/docs/RESULTS.md
ISNAD weakest-link (lenient) 0.761 0.331 opt-in lenient_unknown=True
shuffled-rank control 0.047 — negative control
majority-class control 0.000 — negative control

Scope limit (read before citing)

This measures chain-grade (isnād) agreement only — not matn (content) verdicts, and not hadith authenticity. "Mawḍūʿ" here is a chain-level flag ("a rejected narrator is present"), not a matn-level "fabricated" verdict.

Provenance & reproducibility

Field Value
Derived from emadjumaah/hadith-kg (CC-BY-4.0)
Source SHA-256 d528084321e715006712e0e2461809a3afc9408065a1d1af90238c8b723815a6
Mapping bench/docs/mapping.md (preregistered, frozen)
Reproduction uv run python -m bench.run --seed 0
Software pip install isnad (Apache-2.0)
Paper arXiv:2607.24117 · DOI 10.48550/arXiv.2607.24117

The mapping caveat (honest, not hidden)

The 12-tier → ISNAD grade mapping is the author's best-effort reading of Ibn Ḥajar's Taqrīb al-Tahdhīb tiers. The project has no external domain reviewer yet; ranks 6–7 and 10–12 are the rows most likely to need a scholar's correction. Any correction is a new mapping version with a new, separately reported number — never a silent edit.

File format

One JSON object per line, prefixed by a # JSON header carrying the source SHA-256, the mapping SHA-256, and the exact invocation. Schema:

sanad_id, hukum, true_grade, predicted_grade, disagreement_bucket, is_complete, has_gap, has_taliq, narrator_rank_nos, mode
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Total file size:
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Paper for alizahidraja/isnad-bench