Abstract
We present an Answer Validation System (AV) based on Textual Entailment and Question Answering. The important features used to develop the AV system are Lexical Textual Entailment, Named Entity Recognition, Question-Answer type analysis, chunk boundary module and syntactic similarity module. The proposed AV system is rule based. We first combine the question and the answer into Hypothesis (H) and the Supporting Text as Text (T) to identify the entailment relation as either “VALIDATED” or “REJECTED”. The important features used for the lexical Textual Entailment module in the present system are: WordNet based unigram match, bigram match and skip-gram. In the syntactic similarity module, the important features used are: subject-subject comparison, subject-verb comparison, object-verb comparison and cross subject-verb comparison. The results obtained from the answer validation modules are integrated using a voting technique. For training purpose, we used the AVE 2008 development set. Evaluation scores obtained on the AVE 2008 test set show 66% precision and 65% F-Score for “VALIDATED” decision.
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Pakray, P., Gelbukh, A., Bandyopadhyay, S. (2011). Answer Validation Using Textual Entailment. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2011. Lecture Notes in Computer Science, vol 6609. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19437-5_29
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