Making a MIRACL: Multilingual Information Retrieval Across a Continuum of Languages
MIRACL (Multilingual Information Retrieval Across a Continuum of Languages) is a multilingual dataset we have built for the WSDM 2023 Cup challenge that focuses on ad hoc retrieval across 18 different languages, which collectively encompass over three billion native speakers around the world. These...
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Zusammenfassung: | MIRACL (Multilingual Information Retrieval Across a Continuum of Languages)
is a multilingual dataset we have built for the WSDM 2023 Cup challenge that
focuses on ad hoc retrieval across 18 different languages, which collectively
encompass over three billion native speakers around the world. These languages
have diverse typologies, originate from many different language families, and
are associated with varying amounts of available resources -- including what
researchers typically characterize as high-resource as well as low-resource
languages. Our dataset is designed to support the creation and evaluation of
models for monolingual retrieval, where the queries and the corpora are in the
same language. In total, we have gathered over 700k high-quality relevance
judgments for around 77k queries over Wikipedia in these 18 languages, where
all assessments have been performed by native speakers hired by our team. Our
goal is to spur research that will improve retrieval across a continuum of
languages, thus enhancing information access capabilities for diverse
populations around the world, particularly those that have been traditionally
underserved. This overview paper describes the dataset and baselines that we
share with the community. The MIRACL website is live at http://miracl.ai/. |
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DOI: | 10.48550/arxiv.2210.09984 |