Summary of Word Sense Disambiguation in Native Spanish: a Comprehensive Lexical Evaluation Resource, by Pablo Ortega et al.
Word Sense Disambiguation in Native Spanish: A Comprehensive Lexical Evaluation Resource
by Pablo Ortega, Jordi Luque, Luis Lamiable, Rodrigo López, Richard Benjamins
First submitted to arxiv on: 30 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach to Word Sense Disambiguation (WSD) in Spanish is proposed, addressing limitations of existing algorithms that rely on external knowledge often biased towards English. The study introduces a new resource for Spanish WSD, comprising a sense inventory and lexical dataset sourced from the Diccionario de la Lengua Española. A state-of-the-art WSD system is also evaluated and compared to current resources. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research helps machines better understand human language by solving ambiguity in words. It’s important for communicating effectively. The problem is that most algorithms use external knowledge, which can be biased towards English and not work well for other languages. To solve this, the study creates a new resource for Spanish WSD, using a dictionary maintained by the Real Academia Española. This could improve translations and make them more accurate. |
