Add Recall@5 regression metric with Multihop30 dataset - #59
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Add Recall@5 regression metric with Multihop30 dataset#59prinskumar-tigergraph wants to merge 1 commit into
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Aug 20, 2026
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- New recall_evaluator.py: computes Recall@K by querying GraphRAG and matching retrieved chunks against ground-truth chunks using embedding cosine similarity (threshold=0.70) or LLM judge
- New run_recall.sh: Docker wrapper to run recall evaluation
- New Multihop30 dataset: 30 multi-hop questions (10 each from HotpotQA, 2WikiMultiHopQA, MuSiQue) with raw text corpus, answers, and ground_truth_chunks.csv for retrieval scoring
- Updated evaluator.py, run_eval.sh: unified --mode parameter replacing --agent + --search-type
- Updated run_setup.sh, setup_graph.py: support for Multihop30 graph setup
- New recall_evaluator.py: computes Recall@K by querying GraphRAG and matching retrieved chunks against ground-truth chunks using embedding cosine similarity (threshold=0.70) or LLM judge - New run_recall.sh: Docker wrapper to run recall evaluation - New Multihop30 dataset: 30 multi-hop questions (10 each from HotpotQA, 2WikiMultiHopQA, MuSiQue) with raw text corpus, answers, and ground_truth_chunks.csv for retrieval scoring - Updated evaluator.py, run_eval.sh: unified --mode parameter replacing --agent + --search-type - Updated run_setup.sh, setup_graph.py: support for Multihop30 graph setup Co-authored-by: Cursor <cursoragent@cursor.com>
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