SapienzaNLP/wsd-hard-benchmark
Data and code for "Nibbling at the Hard Core of Word Sense Disambiguation" (ACL 2022).
This project offers a collection of improved and challenging test sets for evaluating how well natural language processing systems can determine the correct meaning of words in context, a task known as Word Sense Disambiguation (WSD). You input sentences with words needing their sense clarified, and the system output is a score indicating how accurately word meanings are assigned. This is primarily for researchers and developers working on refining AI models for language understanding.
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Use this if you are a researcher or developer who needs to rigorously test and identify weaknesses in state-of-the-art AI models designed for understanding word meanings in text, especially for difficult or less common senses.
Not ideal if you are looking for a pre-trained, ready-to-use tool to perform Word Sense Disambiguation on your own text, as this project focuses on evaluation benchmarks rather than a deployable system.
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Mar 25, 2022
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