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Chinese Word Segmentation and Named Entity
Recognition: A Pragmatic Approach
Jianfeng Gao Mu Li
Microsoft Research Asia∗ Microsoft Research Asia*
Andi Wu Chang-Ning Huang
GrapeCity Inc.+ Microsoft Research Asia*
This paper presents a pragmatic approach to Chinese word segmentation. It differentiates from
most of the previous approaches mainly in three respects. First of all, while theoretical linguists
have defined Chinese words with various linguistic criteria, Chinese words in this study are
defined pragmatically as segmentation units whose definition depends on how they are used
and processed in realistic computer applications. Secondly, we propose a pragmatic mathemati-
cal framework in which segmenting known words and detecting unknown words of different
types (i.e. morphologically derived words, factoids, named entities, and other unlisted words)
can be performed simultaneously in a unified way. These tasks are usually conducted sepa-
rately in other systems. Finally, we do not assume the existence of a universal word segmenta-
tion standard which is application independent. Instead, we argue for the necessity of multiple
segmentation standards due to the pragmatic fact that different NLP applications might re-
quire different granularities of Chinese words.
These pragmatic approaches have been implemented in an adaptive Chinese word seg-
menter, called MSRSeg, which will be described in detail. It consists of two components: (1) a
generic segmenter that is based on the framework of linear mixture models, and provides a uni-
fied approach to the five fundamental features of word-level Chinese language processing: lexi-
con word processing, morphological analysis
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