Quantitative evaluation of passage retrieval algorithms for question answering
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We study the impact of using thesaurus-based query expansion methods at the Information Retrieval (IR) stage of a Question Answering (QA) system. We focus on expanding queries for questions regarding actions and events, where verbs have a central role. Two different thesaurus are used: the OpenOffice thesaurus and an automatically generated verb thesaurus. The performance of thesaurus-based methods is compared against what is obtained by (i) executing no expansion and (ii) applying a simple query generalization method. Results show that thesaurus-based approaches help improving recall at retrieval, while keeping satisfactory precision. However, we confirm that positive impact for the final QA performance is mostly achieved due to increase in recall, which can also be obtained by using simpler methods. Nevertheless, because of its better relative precision thesaurus-based expansion is effective in selectively reducing the number of irrelevant text passages retrieved, thus reducing computational load in the answer extraction stage.