Paper: Encoding Semantic Resources in Syntactic Structures for Passage Reranking

ACL ID E14-1070
Title Encoding Semantic Resources in Syntactic Structures for Passage Reranking
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

In this paper, we propose to use seman- tic knowledge from Wikipedia and large- scale structured knowledge datasets avail- able as Linked Open Data (LOD) for the answer passage reranking task. We represent question and candidate answer passages with pairs of shallow syntac- tic/semantic trees, whose constituents are connected using LOD. The trees are pro- cessed by SVMs and tree kernels, which can automatically exploit tree fragments. The experiments with our SVM rank algo- rithm on the TREC Question Answering (QA) corpus show that the added relational information highly improves over the state of the art, e.g., about 15.4% of relative im- provement in P@1.