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        <title>Experiments in Candidate Phrase Selection for Financial Named Entity Extraction - A Demo</title>
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    <abstract>In this study we develop a system that tags and extracts financial concepts called financial named entities (FNE) along with corresponding numeric values – monetary and temporal. We employ machine learning and natural language processing methods to identify financial concepts and dates, and link them to numerical entities.</abstract>
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%0 Conference Proceedings
%T Experiments in Candidate Phrase Selection for Financial Named Entity Extraction - A Demo
%A Kumar, Aman
%A Alam, Hassan
%A Werner, Tina
%A Vyas, Manan
%Y Watanabe, Hideo
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F kumar-etal-2016-experiments
%X In this study we develop a system that tags and extracts financial concepts called financial named entities (FNE) along with corresponding numeric values – monetary and temporal. We employ machine learning and natural language processing methods to identify financial concepts and dates, and link them to numerical entities.
%U https://aclanthology.org/C16-2010
%P 45-48

Markdown (Informal)

[Experiments in Candidate Phrase Selection for Financial Named Entity Extraction - A Demo](https://aclanthology.org/C16-2010) (Kumar et al., COLING 2016)

• Experiments in Candidate Phrase Selection for Financial Named Entity Extraction - A Demo (Kumar et al., COLING 2016)

ACL

• Aman Kumar, Hassan Alam, Tina Werner, and Manan Vyas. 2016. Experiments in Candidate Phrase Selection for Financial Named Entity Extraction - A Demo. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations, pages 45–48, Osaka, Japan. The COLING 2016 Organizing Committee.