The MQ2008 dataset is a dataset for Learning to Rank. It contains 800 queries with labelled documents.
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The Yahoo! Learning to Rank Challenge dataset consists of 709,877 documents encoded in 700 features and sampled from query logs of the Yahoo! search engine, spanning 29,921 queries.
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Publicly available dataset of naturally occurring factual claims for the purpose of automatic claim verification. It is collected from 26 fact checking websites in English, paired with textual sources and rich metadata, and labelled for veracity by human expert journalists.
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Retrieval Question-Answering (ReQA) benchmark tests a model’s ability to retrieve relevant answers efficiently from a large set of documents.
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ART consists of over 20k commonsense narrative contexts and 200k explanations.
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