Experiments in passage selection and answer identification for question answering

Abstract

Question Answering (QA) aims at providing users with short text units that answer specific, well-formed natural language questions. A two stage architecture is widely adopted for this task consisting of a document retrieval step followed by an answer extraction step. In such an approach two main problems need to be addressed to reduce the search space: better selecting answer bearing passages in the document retrieval step and better pinpointing answers in the answer extraction step. We investigate the effect of word-based and linguistic-based features for the identification of answer-bearing sentences and answer candidates in a QA system and show that both play a significant role. © Springer-Verlag Berlin Heidelberg 2006.