allenai/cochrane_sparse_max

This is a copy of the Cochrane dataset, except the input source documents of its validation split have been replaced by a sparse retriever. The retrieval pipeline used:

• query: The target field of each example
• corpus: The union of all documents in the train, validation and test splits. A document is the concatenation of the title and abstract.
• retriever: BM25 via PyTerrier with default settings
• top-k strategy: "max", i.e. the number of documents retrieved, k, is set as the maximum number of documents seen across examples in this dataset, in this case k==25

Retrieval results on the train set:

Recall@100	Rprec	Precision@k	Recall@k
0.7014	0.3841	0.1698	0.5471

Retrieval results on the validation set:

Recall@100	Rprec	Precision@k	Recall@k
0.7226	0.4023	0.1729	0.5676

Retrieval results on the test set:

N/A. Test set is blind so we do not have any queries.