We present in this chapter a description of the major components of a Question-Answering system which has fared well in the three TREC QA evaluations so far, and is currently participating in the ARDA AQUAINT program. Our approach centres around the technique of Predictive Annotation, in which an extended set of named entities is recognized prior to indexing, so that the semantic class labels can be indexed along with text and included in the query string. In addition we present other techniques that are employed for specific question types, such as Virtual Annotation for definition questions. We describe the Answer Selection component, which extracts and ranks answer candidates from the passages returned by the search engine based on linguistic as well as statistical features. We present numerous examples as well as quantitative evaluations.
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Prager, J., Chu-Carroll, J., Brown, E.W., Czuba, K. (2008). Question Answering By Predictive Annotation. In: Strzalkowski, T., Harabagiu, S.M. (eds) Advances in Open Domain Question Answering. Text, Speech and Language Technology, vol 32. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-4746-6_10
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