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GLADIS: A General and Large Acronym Disambiguation Benchmark

  • Institut Polytechnique de Paris
  • Université Paris-Saclay

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collectionContribution à une conférenceRevue par des pairs

Résumé

Acronym Disambiguation (AD) is crucial for natural language understanding on various sources, including biomedical reports, scientific papers, and search engine queries. However, existing acronym disambiguation benchmarks and tools are limited to specific domains, and the size of prior benchmarks is rather small. To accelerate the research on acronym disambiguation, we construct a new benchmark named GLADIS with three components: (1) a much larger acronym dictionary with 1.5M acronyms and 6.4M long forms; (2) a pre-training corpus with 160 million sentences; (3) three datasets that cover the general, scientific, and biomedical domains. We then pre-train a language model, AcroBERT, on our constructed corpus for general acronym disambiguation, and show the challenges and values of our new benchmark.

langue originaleAnglais
titreEACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference
EditeurAssociation for Computational Linguistics (ACL)
Pages2065-2080
Nombre de pages16
ISBN (Electronique)9781959429449
Les DOIs
étatPublié - 1 janv. 2023
Evénement17th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2023 - Dubrovnik, Croatie
Durée: 2 mai 20236 mai 2023

Série de publications

NomEACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference

Une conférence

Une conférence17th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2023
Pays/TerritoireCroatie
La villeDubrovnik
période2/05/236/05/23

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