jorge-martinez-gil/uwsd

Context-Aware Semantic Similarity Measurement for Unsupervised Word Sense Disambiguation

29
/ 100
Experimental

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.

No commits in the last 6 months.

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.

text-analysis language-understanding content-accuracy information-retrieval semantic-search
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 5 / 25

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Stars

16

Forks

1

Language

Python

License

MIT

Last pushed

Jul 14, 2025

Commits (30d)

0

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