NDLI: Extended Named Entity Recognition using Bidirectional LSTM CRF Model

Content Provider	Semantic Scholar
Author	Na, Seong-Won Yoon, Kyoungro
Copyright Year	2018
Abstract	One important field of natural language processing is the Named entity recognition. In named entity recognition, various nouns are recognized as several types of semantic role, such as person, location, organization and others. However, various names are still not recognized as persons, and we want to extend the named entity recognition so that they can be properly recognized as persons. To do this, we modified the NER dataset to fit our purpose and we created our own test dataset to evaluate the model. We trained and evaluated the most commonly used BidirectionalLSTM-CRF models and the CoNLL2003 dataset in the NER problem, so that more nouns can be recognized as persons.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://iaser.org/Vol-6/06EEECS154.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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