iit-patna-cse-ai/GenBench_coding

Task types by split

task_type	train	test
coding_variant	101	8
conservation_reasoning	624	132
counterfactual	598	202
disease_reasoning	523	93
hallucination_detection	627	173
interaction_propagation	651	149
path_traversal	263	151
structural_effect	677	112

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() to resolve full node/edge attributes beyond what's inlined in each item.

Source

Generated from GenBench:

• train: data\hf_generated\splits_v6\train_coding.jsonl
• test: data\hf_generated\splits_v6\test_coding.jsonl