MessIRve: A Large-Scale Spanish Information Retrieval Dataset
Universidad de Buenos Aires, Instituto Tecnológico de Buenos Aires and Universidad de Buenos Aires · Computer Science Department, University of Buenos Aires · University of California, Santa Barbara · quantit · Universidad de San Andres and Universidad de Buenos Aires
PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2025.emnlp-main.1412 ↗
摘要
Information retrieval (IR) is the task of finding relevant documents in response to a user query. Although Spanish is the second most spoken native language, there are few Spanish IR datasets, which limits the development of information access tools for Spanish speakers. We introduce MessIRve, a large-scale Spanish IR dataset with almost 700,000 queries from Google’s autocomplete API and relevant documents sourced from Wikipedia. MessIRve’s queries reflect diverse Spanish-speaking regions, unlike other datasets that are translated from English or do not consider dialectal variations. The large size of the dataset allows it to cover a wide variety of topics, unlike smaller datasets. We provide a comprehensive description of the dataset, comparisons with existing datasets, and baseline evaluations of prominent IR models. Our contributions aim to advance Spanish IR research and improve information access for Spanish speakers.