Publikation
DFKI-LT at QAST 2007: Adapting QA Components to Mine Answers in Speech Transcripts
Bogdan Sacaleanu; Günter Neumann; Christian Spurk
In: A. Nardi; C. Peters (Hrsg.). In online proceedings of CLEF 2007 Working Notes. Conference and Labs of the Evaluation Forum (CLEF), Online-Proceedings, 2007.
Zusammenfassung
The paper describes QAst-v1 a robust question answering system for answering factoid questions in manual and automatic transcriptions of speech. Our system is an adaptation of our text based crosslingual open-domain QA system that we used for the Clef main tasks. In particular we assume that good answer candidates to factoid questions are named entities which are type-compatible with the expected answer type of the question. The main features of QAst-v1 are: use of preemptive off-line annotation of speech transcripts with sentence boundaries, chunk structures and named entities (NEs); construction of a fulltext search index using words and all found NEs; use of robust Wh-analysis component to determine shallow dependency structures, recognition of NEs, and expected answer type (EAT); use of EAT-driven retrieval of sentences and answer candidates; use of redundancy as an indicator of good answer candidates. The main focus of our effort was on the technical realization of a first QAST research prototype making use of as many of our existing QA components as possible. The results of evaluating the system's performance by QAST 2007 were as follows: for subtask T1 (Question-Answering in manual transcriptions of lectures) we achieved an overall accuracy (ACC) of 15% and a mean reciprocal rank (MRR) of 0.17; for subtask T2 (Question-Answering in automatic transcriptions of lectures) we obtained 9% (ACC) and 0.09 (MRR).