FULL-FLEDGED SEMANTIC ANALYSIS AS A TOOL FOR RESOLVING TRIANGLE-COPA SOCIAL SCENARIOS

Abstract

Text interpretation often requires common sense knowledge and reasoning. A convenient tool for developing methods of common sense reasoning are special sets of challenge problems whose interpretation requires sophisticated reasoning. An interesting example is a recently published data set called Triangle Choice of Plausible Alternatives (Triangle-COPA), which contains 100 multiple-choice problems that test the interpretation of social scenarios. Each problem includes a statement and two alternatives. The task is to identify the more plausible alternative. For processing Triangle-COPA data we use SemETAP, a general purpose semantic analyzer. We implement the full scenario of NL understanding starting from NL texts and not from manually composed simplified logical formulas, which is a common practice in logic-based approaches to common sense reasoning. We produce Enhanced Semantic Structures of the statement and both alternatives and check which alternative manifests more semantic agreement with the statement in terms of inferences.