Chinese Chunking Based on Maximum Entropy Markov Models

This paper presents a new Chinese chunking method based on maximum entropy Markov models. We firstly present two types of Chinese chunking specifications and data sets, based on which the chunking models are applied. Then we describe the hidden Markov chunking model and maximum entropy chunking model. Based on our analysis of the two models, we propose a maximum entropy Markov chunking model that combines the transition probabilities and conditional probabilities of states. Experimental results for two types of data sets show that this approach achieves impressive accuracy in terms of the F-score: 91.02% and 92.68%, respectively. Compared with the hidden Markov chunking model and maximum entropy chunking model, based on the same data set, the new chunking model achieves better performance.

[1]  Zhang Yu.  Automatic Identification of Chinese Base Phrases , 2002 .

[2]  Zhao Jun.  THE MODEL FOR CHINESE BASENP STRUCTURE ANALYSIS , 1999 .

[3]  Jianfeng Gao,et al.  Toward a unified approach to statistical language modeling for Chinese , 2002, TALIP.

[4]  Antal van den Bosch,et al.  Shallow Parsing on the Basis of Words Only: A Case Study , 2002, ACL.

[5]  Alexandra Kinyon.  A Language-Independent Shallow-Parser Compiler , 2001, ACL.

[6]  Xiaoqiang Luo.  A Maximum Entropy Chinese Character-Based Parser , 2003, EMNLP.

[7]  Li Su.  Chunk Parsing with Maximum Entropy Principle , 2003 .

[8]  Pascale Fung,et al.  A maximum-entropy chinese parser augmented by transformation-based learning , 2004, TALIP.

[9]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[10]  Jianfeng Gao,et al.  Chinese Chunking with Another Type of Spec , 2004, SIGHAN@ACL.

[11]  Yu Shi,et al.  The Basic Processing of Contemporary Chinese Corpus at Peking University SPECIFICATION , 2002 .

[12]  Miles Osborne,et al.  Shallow Parsing as Part-of-Speech Tagging , 2000, CoNLL/LLL.

[13]  Ralph Weischedel,et al.  A statistical parser for Chinese , 2002 .

[14]  Dan Roth,et al.  Exploring evidence for shallow parsing , 2001, CoNLL.

[15]  David Chiang,et al.  Two Statistical Parsing Models Applied to the Chinese Treebank , 2000, ACL 2000.

[16]  Adwait Ratnaparkhi,et al.  A Maximum Entropy Model for Part-Of-Speech Tagging , 1996, EMNLP.

[17]  Mitchell P. Marcus,et al.  Text Chunking using Transformation-Based Learning , 1995, VLC@ACL.

[18]  Rob Koeling.  Chunking with Maximum Entropy Models , 2000, CoNLL/LLL.

[19]  Adam L. Berger,et al.  A Maximum Entropy Approach to Natural Language Processing , 1996, CL.

[20]  John D. Lafferty,et al.  Inducing Features of Random Fields , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Nianwen Xue,et al.  Developing Guidelines and Ensuring Consistency for Chinese Text Annotation , 2000, LREC.

[22]  Yuji Matsumoto,et al.  Use of Support Vector Learning for Chunk Identification , 2000, CoNLL/LLL.

[23]  Andrew McCallum,et al.  Maximum Entropy Markov Models for Information Extraction and Segmentation , 2000, ICML.

[24]  Steven Abney,et al.  Parsing By Chunks , 1991 .

[25]  Byoung-Tak Zhang,et al.  Text Chunking by Combining Hand-Crafted Rules and Memory-Based Learning , 2003, ACL.

[26]  Sabine Buchholz,et al.  Introduction to the CoNLL-2000 Shared Task Chunking , 2000, CoNLL/LLL.

[27]  Beatrice Santorini,et al.  Building a Large Annotated Corpus of English: The Penn Treebank , 1993, CL.

[28]  Changning Huang,et al.  A Unified Statistical Model for the Identification of English BaseNP , 2000, ACL.

[29]  Anthony Kroch,et al.  The Bracketing Guidelines for the Penn Chinese Treebank (3.0) , 2000 .