J-MADRAL/AmazonESCI

Amazon ESCI is a large-scale test collection for product search, comprising: (i) a corpus of 1.2M products of the english portion of Amazon ESCI (ii) a set of queries with 74.9k, 13.5k, and 8.9k queries in the training, validation, and test sets, respectively. The relevance judgements comprise 20.15 assessments per query on average, divided in four relevance labels: Exact, Substitute, Complementary, and Irrelevant, with gains of 1.0, 0.1, 0.01, and 0.0 associated. Only Exact products are… See the full description on the dataset page: https://huggingface.co/datasets/J-MADRAL/AmazonESCI.