Predicting the uncertainty of sentiment adjectives in indirect answers

Authors:
Mitra Mohtarami;Hadi Amiri;Man Lan;Chew Lim Tan
Affiliations:
School of Computing, National University of Singapore, Singapore, Singapore;School of Computing, National University of Singapore, Singapore, Singapore;Institute for Infocomm Research, Singapore, Singapore;School of Computing, National University of Singapore, Singapore, Singapore
Venue:
Proceedings of the 20th ACM international conference on Information and knowledge management
Year:
2011

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Abstract

Opinion question answering (QA) requires automatic and correct interpretation of an answer relative to its question. However, the ambiguity that often exists in the question-answer pairs causes complexity in interpreting the answers. This paper aims to infer yes/no answers from indirect yes/no question-answer pairs (IQAPs) that are ambiguous due to the presence of ambiguous sentiment adjectives. We propose a method to measure the uncertainty of the answer in an IQAP relative to its question. In particular, to infer the yes or no response from an IQAP, our method employs antonyms, synonyms, word sense disambiguation as well as the semantic association between the sentiment adjectives that appear in the IQAP. Extensive experiments demonstrate the effectiveness of our method over the baseline.