Datasets:

Prajjit
/

CodeMixCheck

# Known limitations: CodeMixCheck v2.2.1

1. **Mostly synthetic.** 6,910 of the 7,254 released rows are template-generated. Their labels are correct *by construction* within a simulated world, and no human checked them row by row. They are not real-world fact-checks.
2. **No evidence corpus.** `evidence_explanation` states the (simulated) evidence in one sentence. A RAG system cannot retrieve it from anywhere.
3. **Semantic overlap across splits** (release audit, no rows removed):
   - fact_verification: 84 claim cores (228 rows) recur across splits under different framing (D01). There are 73 near-duplicate cross-split pairs at fuzz.ratio ≥ 90, mostly template siblings with a different entity.
   - sentiment (synthetic): 36 train/validation near-duplicate pairs.
   - abuse_detection: 57 cross-split near-duplicate pairs (train, validation and test are typo/emoji variants of a small set of base comments).
   - Implication: synthetic validation/test scores overestimate generalisation. Use the strict filter (587 of 661 `test_synthetic` rows) and `test_curated`.
4. **Generator artefacts.** Emoji, hashtags, typo patterns and frame templates repeat. Models may pick up surface cues. Rows with an `unparsed` frame are mostly `True` (589 of 845).
5. **Small auxiliary tasks.** Public sentiment has 128 rows (train 98 / validation 30, **no test split**; the human-collected test set is not released). Abuse has 122 rows (67 / 27 / 28). Neither is representative of naturally occurring sentiment or abuse.
6. **Curated test label skew.** Hearsay is 100% `Unverifiable` and health/lifestyle is 90% `True`. Across `test_curated` there are only 30 `False` and 15 `Partially True` rows. Report results per `eval_subset`.
7. **Missing explanations.** 129 curated rows have no `evidence_explanation` after the v2.2.1 relabel.
8. **No source references** for curated claims (paraphrased; sources not recorded).
9. **Incomplete version history.** 782 retired IDs have no recorded reason.
10. **Narrow coverage.** The data is Tamil Nadu-centric, and Romanisation follows one set of conventions. Sri Lankan, Malaysian, Singaporean and diaspora Tamil are not represented.
11. **Single annotator.** There is no inter-annotator agreement study.

	# Known limitations: CodeMixCheck v2.2.1

	1. Mostly synthetic. 6,910 of the 7,254 released rows are template-generated. Their labels are correct by construction within a simulated world, and no human checked them row by row. They are not real-world fact-checks.
	2. No evidence corpus. `evidence_explanation` states the (simulated) evidence in one sentence. A RAG system cannot retrieve it from anywhere.
	3. Semantic overlap across splits (release audit, no rows removed):
	- fact_verification: 84 claim cores (228 rows) recur across splits under different framing (D01). There are 73 near-duplicate cross-split pairs at fuzz.ratio ≥ 90, mostly template siblings with a different entity.
	- sentiment (synthetic): 36 train/validation near-duplicate pairs.
	- abuse_detection: 57 cross-split near-duplicate pairs (train, validation and test are typo/emoji variants of a small set of base comments).
	- Implication: synthetic validation/test scores overestimate generalisation. Use the strict filter (587 of 661 `test_synthetic` rows) and `test_curated`.
	4. Generator artefacts. Emoji, hashtags, typo patterns and frame templates repeat. Models may pick up surface cues. Rows with an `unparsed` frame are mostly `True` (589 of 845).
	5. Small auxiliary tasks. Public sentiment has 128 rows (train 98 / validation 30, no test split; the human-collected test set is not released). Abuse has 122 rows (67 / 27 / 28). Neither is representative of naturally occurring sentiment or abuse.
	6. Curated test label skew. Hearsay is 100% `Unverifiable` and health/lifestyle is 90% `True`. Across `test_curated` there are only 30 `False` and 15 `Partially True` rows. Report results per `eval_subset`.
	7. Missing explanations. 129 curated rows have no `evidence_explanation` after the v2.2.1 relabel.
	8. No source references for curated claims (paraphrased; sources not recorded).
	9. Incomplete version history. 782 retired IDs have no recorded reason.
	10. Narrow coverage. The data is Tamil Nadu-centric, and Romanisation follows one set of conventions. Sri Lankan, Malaysian, Singaporean and diaspora Tamil are not represented.
	11. Single annotator. There is no inter-annotator agreement study.