DFKI-LT at AVE 2007: Using Recognizing Textual Entailment for Answer Validation

Rui Wang, Günter Neumann

In: A. Nardi , C. Peters (Hrsg.). Online proceedings of CLEF 2007 Working Notes. Conference and Labs of the Evaluation Forum (CLEF) Online-Proceedings 9/2007.


This report is about our participation in the Answer Validation Exercise (AVE) 2007. Our system utilizes a Recognizing Textual Entailment (RTE) system as a component to validate answers. We first change the question and the answer into Hypothesis (H) and view the document as Text (T), in order to cast the AVE task into a RTE problem. Then, we use our RTE system to tell us whether the entailment relation holds between the documents (i.e. Ts) and question-answer pairs (i.e. Hs). Finally, we adapt the results for the AVE task. In all, we have submitted two runs and achieved f-measures of 0.46 and 0.55 respectively, which both outperform last year's best result for English. After detailed error analysis, we have found that both the recall and the precision of our system could be improved in the future.

WangCLEF2007.pdf (pdf, 169 KB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence