Paper: Using Semantic Roles to Improve Question Answering

ACL ID D07-1002
Title Using Semantic Roles to Improve Question Answering
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007

Shallow semantic parsing, the automatic identification and labeling of sentential con- stituents, has recently received much atten- tion. Our work examines whether seman- tic role information is beneficial to question answering. We introduce a general frame- work for answer extraction which exploits semantic role annotations in the FrameNet paradigm. We view semantic role assign- ment as an optimization problem in a bipar- tite graph and answer extraction as an in- stance of graph matching. Experimental re- sults on the TREC datasets demonstrate im- provements over state-of-the-art models.