Hungarian named entity recognition with a maximum entropy approach

Varga Dániel and Simon Eszter: Hungarian named entity recognition with a maximum entropy approach. In: Acta cybernetica, (18) 2. pp. 293-301. (2007)

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Abstract

In the analysis of natural language text a key step is named entity recognition, finding all complex noun phrases that denote persons, organizations, locations, and other entities designated by a name. In this paper we introduce the hunner open source language-independent named entity recognition system, and present results for Hungarian. When the input to hunner is already morphologically analyzed, we apply the system together with the hunpos morphological disambiguator, but hunner is also capable of working on raw (morphologically unanalyzed) text.

Item Type: Article
Journal or Publication Title: Acta cybernetica
Date: 2007
Volume: 18
Number: 2
ISSN: 0324-721X
Page Range: pp. 293-301
Language: English
Place of Publication: Szeged
Event Title: Conference on Hungarian Computational Linguistics (4.) (2006) (Szeged)
Related URLs: http://acta.bibl.u-szeged.hu/38524/
Uncontrolled Keywords: Számítástechnika, Nyelvészet - számítógép alkalmazása
Additional Information: Bibliogr.: p. 300-301. ; összefoglalás angol nyelven
Subjects: 01. Natural sciences
01. Natural sciences > 01.02. Computer and information sciences
06. Humanities
06. Humanities > 06.02. Languages and Literature
Date Deposited: 2016. Oct. 15. 12:25
Last Modified: 2022. Jun. 16. 14:13
URI: http://acta.bibl.u-szeged.hu/id/eprint/12817

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