SapienzaNLP/xl-wsd-code
Code to train and test Word Sense Disambiguation models based on different pretrained transformers.
This project helps natural language processing researchers train and evaluate custom word sense disambiguation (WSD) models. You provide textual data with ambiguous words and their correct sense labels, and it outputs a model that can identify the correct meaning of words in new text. It is designed for NLP researchers and computational linguists working on improving machine understanding of language.
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Use this if you need to build or assess state-of-the-art models for resolving word ambiguities in various languages, tailored to specific datasets.
Not ideal if you are looking for a ready-to-use WSD tool or an API to integrate into an application without custom model training.
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Python
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Last pushed
Dec 21, 2021
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