University of Pittsburgh

+/-EffectWordNet: Sense-level Lexicon Acquisition for Opinion Inference

Graduate Student
Friday, October 10, 2014 - 1:00pm - 1:30pm

Recently, work in NLP was initiated on a type of opinion inference that arises when opinions are expressed toward events which have positive or negative effects on entities (+/-effect events). This paper addresses methods for creating a lexicon of such events, to support such work on opinion inference.  Due to significant sense ambiguity, our goal is to develop a sense-level rather than word-level lexicon. To maximize the effectiveness of different types of information, we combine a graph-based method using WordNet relations and a standard classifier using gloss information. A hybrid between the two gives the best results. Further, we provide evidence that the model is an effective way to guide manual annotation to find +/-effect senses that are not in the seed set.

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