GLADIS: A General and Large Acronym Disambiguation Benchmark - Laboratoire Traitement et Communication de l'Information Access content directly
Conference Papers Year : 2023

GLADIS: A General and Large Acronym Disambiguation Benchmark

Abstract

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.
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hal-04039173 , version 1 (21-03-2023)

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  • HAL Id : hal-04039173 , version 1

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Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek. GLADIS: A General and Large Acronym Disambiguation Benchmark. EACL 2023 - The 17th Conference of the European Chapter of the Association for Computational Linguistics, May 2023, Dubrovnik, Croatia. ⟨hal-04039173⟩
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