| Institute of Informatics>>> Acta Cybernetica>>> Past Issues>>> Volume 18, Number 2, 2007>>> |
 Magyarul
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Hungarian named entity recognition with a maximum entropy approach
Abstract (in LaTeX format)
In the analysis of natural language text a key step is {\it 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 {\tt hunner} open source language-independent named entity recognition system, and present results for Hungarian. When the input to {\tt hunner} is already morphologically analyzed, we apply the system together with the {\tt hunpos} morphological disambiguator, but {\tt hunner} is also capable of working on raw (morphologically unanalyzed) text.
Keywords: natural language processing, computational linguistics, named entity recognition.
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BibTeX entry
@ARTICLE{Varga:2007:ActaCybernetica,author = {D\'aniel Varga and Eszter Simon},
title = {Hungarian named entity recognition with a maximum entropy approach},
journal = {Acta Cybernetica},
year = {2007},
volume = {18},
pages = {293--301},
number = {2},
abstract = {In the analysis of natural language text a key step is {\it 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 {\tt hunner} open source language-independent named entity recognition system, and present results for Hungarian. When the input to {\tt hunner} is already morphologically analyzed, we apply the system together with the {\tt hunpos} morphological disambiguator, but {\tt hunner} is also capable of working on raw (morphologically unanalyzed) text.},
keywords = {natural language processing, computational linguistics, named entity recognition}
}