Named Entity Recognition

Named Entity Recognition (NER) automatically identifies words or phrases of a special meaning in texts and classifies them into groups (e.g. persons, organizations, products, dates, cities, coutnries, product names). We have successfully employed a modern BERT-like model focused on Czech language.

Publications

The Second Cross-Lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic Languages
Jakub Piskorski Laska Laskova Michał Marcińczuk Lidia Pivovarova Pavel Přibáň and Josef Steinberger and Roman Yangarber
Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing (2019)
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Named Entity Recognition
First Steps in Czech Entity Linking
Michal Konkol
Text, Speech, and Dialogue (2015)
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Named Entity Recognition
Named entities as new features for Czech document classification
Pavel Král
15th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2014) (2014)
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Document Classification | Named Entity Recognition
UWB: Machine Learning Approach to Aspect-Based Sentiment Analysis
Tomáš Brychcín and Michal Konkol Josef Steinberger
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014) (2014)
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Semantic Analysis | Sentiment Analysis | Named Entity Recognition
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