Exploiting Syntactic and Shallow Semantic Kernels for Question Answer Classification

A. Moschitti, S. Quarteroni, R. Basili, S. Manandhar

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We study the impact of syntactic and shallow semantic information in automatic classifi- cation of questions and answers and answer re-ranking. We define (a) new tree struc- tures based on shallow semantics encoded in Predicate Argument Structures (PASs) and (b) new kernel functions to exploit the representational power of such structures with Support Vector Machines. Our ex- periments suggest that syntactic information helps tasks such as question/answer classifi- cation and that shallow semantics gives re- markable contribution when a reliable set of PASs can be extracted, e.g. from answers.
Original languageEnglish
Title of host publicationProceedings of 45th Annual meeting of the Association for Computational Linguistics
Number of pages7
Publication statusPublished - 2007
EventACL 2007 - Prague, Czech Republic
Duration: 23 Jun 200730 Jun 2007


ConferenceACL 2007
CityPrague, Czech Republic

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