Word Sense Disambiguation in Native Spanish: A Comprehensive Lexical Evaluation Resource
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866910625424211968 |
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| author | Ortega, Pablo Luque, Jordi Lamiable, Luis López, Rodrigo Benjamins, Richard |
| author_facet | Ortega, Pablo Luque, Jordi Lamiable, Luis López, Rodrigo Benjamins, Richard |
| contents | Human language, while aimed at conveying meaning, inherently carries ambiguity. It poses challenges for speech and language processing, but also serves crucial communicative functions. Efficiently solve ambiguity is both a desired and a necessary characteristic. The lexical meaning of a word in context can be determined automatically by Word Sense Disambiguation (WSD) algorithms that rely on external knowledge often limited and biased toward English. When adapting content to other languages, automated translations are frequently inaccurate and a high degree of expert human validation is necessary to ensure both accuracy and understanding. The current study addresses previous limitations by introducing a new resource for Spanish WSD. It includes a sense inventory and a lexical dataset sourced from the Diccionario de la Lengua Española which is maintained by the Real Academia Española. We also review current resources for Spanish and report metrics on them by a state-of-the-art system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_20524 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Word Sense Disambiguation in Native Spanish: A Comprehensive Lexical Evaluation Resource Ortega, Pablo Luque, Jordi Lamiable, Luis López, Rodrigo Benjamins, Richard Computation and Language Artificial Intelligence Human language, while aimed at conveying meaning, inherently carries ambiguity. It poses challenges for speech and language processing, but also serves crucial communicative functions. Efficiently solve ambiguity is both a desired and a necessary characteristic. The lexical meaning of a word in context can be determined automatically by Word Sense Disambiguation (WSD) algorithms that rely on external knowledge often limited and biased toward English. When adapting content to other languages, automated translations are frequently inaccurate and a high degree of expert human validation is necessary to ensure both accuracy and understanding. The current study addresses previous limitations by introducing a new resource for Spanish WSD. It includes a sense inventory and a lexical dataset sourced from the Diccionario de la Lengua Española which is maintained by the Real Academia Española. We also review current resources for Spanish and report metrics on them by a state-of-the-art system. |
| title | Word Sense Disambiguation in Native Spanish: A Comprehensive Lexical Evaluation Resource |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2409.20524 |