Ranking suspected answers to natural language questions using predictive annotation
<|reference_start|>Ranking suspected answers to natural language questions using predictive annotation: In this paper, we describe a system to rank suspected answers to natural language questions. We process both corpus and query using a new technique, predictive annotation, which augments phrases in texts with labels anticipating their being targets of certain kinds of questions. Given a natural language question, an IR system returns a set of matching passages, which are then analyzed and ranked according to various criteria described in this paper. We provide an evaluation of the techniques based on results from the TREC Q&A evaluation in which our system participated.<|reference_end|>
@article{radev2000ranking,
    title={Ranking suspected answers to natural language questions using predictive
  annotation},
    author={Dragomir R. Radev (University of Michigan), John Prager (IBM TJ Watson
  Research Center), Valerie Samn (Teachers College, Columbia University)},
    journal={ANLP'00, Seattle, WA, May 2000},
    year={2000},
    archivePrefix={arXiv},
    eprint={cs/0005029},
    primaryClass={cs.CL}
}