JOURNAL ARTICLE

Named Entity Recognition from Turkish texts

Abstract

Named Entity Recognition is an important subject of Natural Language Processing and is used to classify proper nouns into different types such as person, location and organization names in addition to formula, date and money definitions. Rule Based Named Entity Recognition means defining rules to classify named entities in a text through using lexical resources and creating patterns. This study focuses on classification of proper nouns into three types including person, location and organization names regardless of the subject of text.

Keywords:
Computer science Natural language processing Named-entity recognition Proper noun Subject (documents) Turkish Artificial intelligence Noun Named entity Entity linking Linguistics Task (project management) Knowledge base World Wide Web

Metrics

6
Cited By
0.00
FWCI (Field Weighted Citation Impact)
10
Refs
0.15
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Text and Document Classification Technologies
Physical Sciences →  Computer Science →  Artificial Intelligence

Related Documents

JOURNAL ARTICLE

Named-entity recognition in Turkish legal texts

Can ÇetindağBerkay YazıcıoğluAykut Koç

Journal:   Natural Language Engineering Year: 2022 Vol: 29 (3)Pages: 615-642
BOOK-CHAPTER

Named Entity Recognition Experiments on Turkish Texts

Dilek KüçükAdnan Yazıcı

Lecture notes in computer science Year: 2009 Pages: 524-535
BOOK-CHAPTER

Turkish Named-Entity Recognition

Reyyan YeniterziGökhan TürKemal Oflazer

Theory and applications of natural language processing Year: 2018 Pages: 115-132
© 2026 ScienceGate Book Chapters — All rights reserved.