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Entities, Dates, and Languages: Zero-Shot on Historical Texts with T0
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In: Proceedings of the International Workshop on Challenges & Perspectives in Creating Large Language Models 2022 (BigScience 2022) ; https://hal.inria.fr/hal-03639144 ; Proceedings of the International Workshop on Challenges & Perspectives in Creating Large Language Models 2022 (BigScience 2022), May 2022, Dublin, France (2022)
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Abstract:
International audience ; In this work, we explore whether the recently demonstrated zero-shot abilities of the T0 model extend to Named Entity Recognition for out-of-distribution languages and time periods. Using a historical newspaper corpus in 3 languages as test-bed, we use prompts to extract possible named entities. Our results show that a naive approach for prompt-based zero-shot multilingual Named Entity Recognition is error-prone, but highlights the potential of such an approach for historical languages lacking labeled datasets. Moreover, we also find that T0-like models can be probed to predict the publication date and language of a document, which could be very relevant for the study of historical texts.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]; [SHS.LANGUE]Humanities and Social Sciences/Linguistics
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URL: https://hal.inria.fr/hal-03639144
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Entities, Dates, and Languages: Zero-Shot on Historical Texts with T0 ...
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