Paper Info
Title
Semantic Extensions of the Ephyra QA System for TREC 2007
Abstract
We describe recent extensions to the Ephyra question answer- ing (QA) system and their evaluation in the TREC 2007 QA track. Existing syntactic answer extraction approaches for factoid and list questions have been complemented with a high-accuracy semantic approach that generates a semantic representation of the question and extracts answer candidates from similar semantic structures in the corpus. Candidates found by different answer extractors are combined and ranked by a statistical framework that integrates a variety of answer validation techniques and similarity measures to estimate a probability for each candidate. A novel answer type classi- fier combines a statistical model and hand-coded rules to pre- dict the answer type based on syntactic and semantic features of the question. Our approach for the 'other' questions uses Wikipedia and Google to judge the relevance of answer can- didates found in the corpora.
Year
Venue
Keywords
2007
TREC
statistical model
Field
DocType
Citations 
Data mining,Question answering,Information retrieval,Ranking,Computer science,Natural language processing,Statistical model,Artificial intelligence,Classifier (linguistics),Semantic representation,Syntax,Factoid
Conference
30
PageRank 
References 
Authors
1.85
22
6
Name
Order
Citations
PageRank
Nico Schlaefer155926.50
Jeongwoo Ko217614.11
Justin Betteridge323811.95
Manas Pathak4302.19
Eric Nyberg51110101.91
Guido Sautter6678.00