Question classification with log-linear models

Question classification has become a crucial step in modern question answering systems. Previous work has demonstrated the effectiveness of statistical machine learning approaches to this problem. This paper presents a new approach to building a question classifier using log-linear models. Evidence from a rich and diverse set of syntactic and semantic features is evaluated, as well as approaches which exploit the hierarchical structure of the question classes.

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

[2]  Christopher D. Manning,et al.  Enriching the Knowledge Sources Used in a Maximum Entropy Part-of-Speech Tagger , 2000, EMNLP.

[3]  Ronald Rosenfeld,et al.  A survey of smoothing techniques for ME models , 2000, IEEE Trans. Speech Audio Process..

[4]  Eduard H. Hovy,et al.  Question Answering in Webclopedia , 2000, TREC.

[5]  Lynette Hirschman,et al.  Natural language question answering: the view from here , 2001, Natural Language Engineering.

[6]  Ulf Hermjakob,et al.  Parsing and Question Classification for Question Answering , 2001, ACL 2001.

[7]  John A. Carroll,et al.  Applied morphological processing of English , 2001, Natural Language Engineering.

[8]  Dan Roth,et al.  Learning Question Classifiers , 2002, COLING.

[9]  Eduard Hovy,et al.  A question/answer typology with surface text patterns , 2002 .

[10]  Rob Malouf,et al.  A Comparison of Algorithms for Maximum Entropy Parameter Estimation , 2002, CoNLL.

[11]  James R. Curran,et al.  Investigating GIS and Smoothing for Maximum Entropy Taggers , 2003, EACL.

[12]  Wayne H. Ward,et al.  Question Classification with Support Vector Machines and Error Correcting Codes , 2003, HLT-NAACL.

[13]  Mark Steedman,et al.  Object-Extraction and Question-Parsing using CCG , 2004, EMNLP.

[14]  James R. Curran,et al.  Parsing the WSJ Using CCG and Log-Linear Models , 2004, ACL.

[15]  Krystle Kocik,et al.  Question Classification using Maximum Entropy Models , 2004 .