Paper Info
Title
Multi-language named-entity recognition system based on HMM
Abstract
We introduce a multi-language named-entity recognition system based on HMM. Japanese, Chinese, Korean and English versions have already been implemented. In principle, it can analyze any other language if we have training data of the target language. This system has a common analytical engine and it can handle any language simply by changing the lexical analysis rules and statistical language model. In this paper, we describe the architecture and accuracy of the named-entity system, and report preliminary experiments on automatic bilingual named-entity dictionary construction using the Japanese and English named-entity recognizer.
Year
DOI
Venue
2003
10.3115/1119384.1119390
NER@ACL
Keywords
Field
DocType
lexical analysis rule,multi-language named-entity recognition system,automatic bilingual named-entity dictionary,target language,preliminary experiment,named-entity system,english version,common analytical engine,english named-entity recognizer,statistical language model
Training set,Architecture,Recognition system,Computer science,Speech recognition,Artificial intelligence,Natural language processing,Lexical analysis,Hidden Markov model,Named-entity recognition,Multi language,Language model
Conference
Volume
Citations 
PageRank 
W03-15
6
0.53
References 
Authors
10
2
Name
Order
Citations
PageRank
Kuniko Saito1757.12
Masaaki Nagata257377.86