Given a question Q and a sentence/paragraph SP that is likely to contain the answer to Q, an answer selection module is supposed to select the “exact” answer sub-string A ⊂ SP. We study three distinct approaches to solving this problem: one approach uses algorithms that rely on rich knowledge bases and sophisticated syntactic/semantic processing; one approach uses patterns that are learned in an unsupervised manner from the web, using computational biology-inspired alignment algorithms; and one approach uses statistical noisy-channel algorithms similar to those used in machine translation. We assess the strengths and weaknesses of these three approaches and show how they can be combined using a maximum entropy-based framework.
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Echihabi, A., Hermjakob, U., Hovy, E., Marcu, D., Melz, E., Ravichandran, D. (2008). How To Select An Answer String?. 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_12
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