GraphRarebench / README.md
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---
pretty_name: GraphRareBench
license: mit
tags:
- rare-disease
- phenotype-driven-diagnosis
- benchmark
- knowledge-graph
- graph-evidence
- hpo
- mondo
---
# GraphRareBench Dataset
This release is the single frozen GraphRareBench benchmark described in the
AAAI 2027 submission. It contains 2,365 ontology-derived
rare-disease ranking cases and 18,093 labeled
target-confounder pairs.
## Layout
```text
dataset/
cases/graphrarebench_cases.jsonl
sidecars/evidence_bundle.jsonl
sidecars/graph_path_alignment.jsonl
metadata/manifest.json
metadata/release_summary.json
metadata/checksums.sha256
schema/case_public_schema.json
schema/evidence_bundle_public_schema.json
provenance/source_provenance.csv
```
## Case File
`cases/graphrarebench_cases.jsonl` is the benchmark anchor. Each row contains:
- `case_id`, `split`, and `partition_strategy`;
- `query_phenotypes`: the coarsened HPO query visible to evaluated methods;
- `candidate_pools.full`: the closed full candidate set;
- `candidate_pools.hard`: the target plus graph-defined hard confounders;
- `target_disease` and `hard_confounders`: evaluator-only labels for scoring;
- `evidence_bundle_id` and `graph_path_alignment_refs` for source-linked audit.
The public split is gene-component-aware: 1,892
train, 236 dev, and 237
test cases. Test cases have a median of 69
full-pool candidates and a median of 5
hard confounders.
## Evaluation
Full-pool ranking uses `candidate_pools.full`. The tool-mediated hard-pool
audit uses `candidate_pools.hard`. Evaluated systems should receive only the
query, candidate IDs/names, and permitted evidence interface; target labels,
hard-confounder labels, and mechanism annotations are evaluator-only.