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2018 | OriginalPaper | Chapter

6. Turkish Named-Entity Recognition

Authors : Reyyan Yeniterzi, Gökhan Tür, Kemal Oflazer

Published in: Turkish Natural Language Processing

Publisher: Springer International Publishing

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Abstract

Named-entity recognition is an important task for many other natural language processing tasks and applications such as information extraction, question answering, sentiment analysis, machine translation, etc. Over the last decades named-entity recognition for Turkish has attracted significant attention both in terms of systems development and resource development. After a brief description of the general named-entity recognition task, this chapter presents a comprehensive overview of the work on Turkish named-entity recognition along with the data resources various research efforts have built.

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previous chapter Turkish Speech Recognition

next chapter Dependency Parsing of Turkish

Note that any suffixes on the last word of a named-entity is split as a separate token.

The evaluation scripts from the CONLL 2000 shared task can be found at www.github.com/newsreader/evaluation/tree/master/nerc-evaluation (Accessed on Sept. 14, 2017).

The entity type counts are different in these studies due to either using different subsets or counting multiple token entities as one or not.

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The data collection used in this study is not exactly the same with data used in Küçük and Yazıcı (2009a,b).

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Title: Turkish Named-Entity Recognition
Authors: Reyyan Yeniterzi
Gökhan Tür
Kemal Oflazer
Publisher: Springer International Publishing
Book: Turkish Natural Language Processing
Print ISBN: 978-3-319-90163-3

Electronic ISBN: 978-3-319-90165-7

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-90165-7_6

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