Semantic Extensions of the Ephyra QA System for TREC 2007

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.