bond005/runne_contrastive_ner
This project is concerned with my participating in the RuNNE competition https://github.com/dialogue-evaluation/RuNNE
This project helps data scientists and NLP engineers accurately identify complex, 'nested' named entities within Russian text. It takes raw Russian text documents and an entity type list, and outputs text with specific words or phrases tagged as entities, even when one entity is part of another. This is for users working with advanced Russian text analysis tasks.
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Use this if you need to extract named entities from Russian text, especially when dealing with nested structures like 'Donetsk National Technical University' where 'Donetsk' is a location within the larger organization name.
Not ideal if your primary need is for named entity recognition in languages other than Russian, or if you only require simple, non-nested entity extraction.
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Language
Python
License
Apache-2.0
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Last pushed
Jun 28, 2023
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