jorge-martinez-gil/uwsd
Context-Aware Semantic Similarity Measurement for Unsupervised Word Sense Disambiguation
This tool helps clarify the intended meaning of ambiguous words in text, like distinguishing between "bank" (river vs. financial). You provide text with multi-sense words, and it outputs the most probable meaning based on context. Anyone working with text data who needs to ensure accurate interpretation, such as in information retrieval or content analysis, would find this useful.
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Use this if you need to automatically resolve the meaning of ambiguous words within sentences to improve the accuracy of text understanding applications.
Not ideal if your primary goal is to perform general natural language processing tasks that don't specifically involve disambiguating word senses.
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Language
Python
License
MIT
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Last pushed
Jul 14, 2025
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