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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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: angol
Event Title: Conference on Hungarian Computational Linguistics, 4., 2006, Szeged
Uncontrolled Keywords: Természettudomány, Informatika, Nyelvtudomány
Additional Information: Bibliogr.: p. 300-301.; Abstract
Date Deposited: 2016. Oct. 15. 12:25
Last Modified: 2018. Jun. 05. 14:20

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