Paper: Ranking Suspected Answers To Natural Language Questions Using Predictive Annotation

ACL ID A00-1021
Title Ranking Suspected Answers To Natural Language Questions Using Predictive Annotation
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2000
Authors

In this paper, we describe a system to rank sus- pected answers to natural language questions. We process both corpus and query using a new technique, predictive annotation, which aug- ments phrases in texts with labels anticipating their being targets of certain kinds of questions. Given a natural language question, our IR sys- tem returns a set of matching passages, which we then rank using a linear function of seven predictor variables. We provide an evaluation of the techniques based on results from the TREC Q&A evaluation in which our system partici- pated.