edoost/pert

Persian Ezafe Recognition Using Transformers and Its Role in Part-Of-Speech Tagging

20
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Experimental

This project helps natural language processing researchers and computational linguists analyze Persian text more accurately. It takes raw Persian text and identifies 'ezafe' constructions, which are a key grammatical feature, helping to correctly tag parts of speech. This improves the foundational understanding of how words function in Persian sentences.

No commits in the last 6 months.

Use this if you are a researcher or developer working on advanced Persian text analysis and need to improve part-of-speech tagging accuracy by specifically recognizing ezafe constructions.

Not ideal if you need a general-purpose Persian text analysis tool for end-users, or if your focus is not on detailed grammatical parsing.

Persian-NLP computational-linguistics part-of-speech-tagging grammatical-analysis text-processing
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 7 / 25

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Last pushed

Nov 15, 2021

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