Encoding Semantic Resources in Syntactic Structures for Passage Reranking

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.