Datasets:
File size: 2,389 Bytes
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license: unknown
task_categories:
- question-answering
tags:
- genomics
- knowledge-graph
- multi-hop-reasoning
- biology
pretty_name: GenBench CoCG QA Dataset
---
# GenBench CoCG QA Dataset
Multi-hop genetic reasoning QA items generated from GenBench's knowledge
graph (Ensembl, ClinVar, VEP, BioGRID, STRING, Reactome, UniProt, GO,
SIGNOR, OmniPath, KEGG, DisGeNET, OpenTargets, PubTator3, GTEx, and more),
built for CoCG (Co-Evolving Confidence Graph) agent training.
**2513 items across 11 task types.**
## Task types
| task_type | count |
|---|---|
| `coding_variant` | 53 |
| `conservation_reasoning` | 246 |
| `counterfactual` | 246 |
| `disease_reasoning` | 246 |
| `evidence_attribution` | 246 |
| `hallucination_detection` | 246 |
| `interaction_propagation` | 246 |
| `mechanistic_explanation` | 246 |
| `path_traversal` | 246 |
| `structural_effect` | 246 |
| `tissue_specific` | 246 |
## Schema
Each item has:
- `id`, `task_type`, `pipeline` (`coding_variant`/`noncoding_regulatory`), `difficulty`
- `question`, `answer`, `choices` (MCQ options, when applicable)
- `context` -- either a templated chain narration, or (if `llm_rewrite` was
applied) an LLM-rewritten fluent Step/Evidence/Interpretation/Conclusion
narrative
- `reasoning_chain` -- the grounded, machine-checkable multi-hop path
(`steps`: each with `source_node_id`/`target_node_id`/`edge_relation`/
`edge_confidence`/`edge_source_db`), never touched by any LLM step
- `modality_data` -- raw modality payloads (sequence, structural,
transcriptomic, post_translational, signaling_role, etc.) attached to the
chain's anchor nodes
- `evidence` -- supporting evidence entries with source database/PMID
- `path_confidence_score` -- continuous, confidence-derived difficulty score
## Companion graph
`graph.json` (if included in this repo) is the exact knowledge graph these
items' `reasoning_chain` node IDs refer to -- load it with
[GenBench's `GraphBuilder.load()`](https://github.com/murk07/GenBench) to
resolve full node/edge attributes beyond what's inlined in each item.
## Source
Generated from `data\curated\qa_dataset.jsonl` in [GenBench](https://github.com/murk07/GenBench),
the substrate for CoCG (Co-Evolving Confidence Graph) agent training --
per-edge, per-modality KG confidence that co-adapts with an RL policy
during training rather than treating the KG as a frozen oracle.
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