ATandT: The TagandParse Approach to Semantic Parsing of Robot Spatial Commands

Abstract

The Tag&Parse approach to semantic parsing first assigns semantic tags to each word in a sentence and then parses the tag sequence into a semantic tree. We use statistical approach for tagging, parsing, and reference resolution stages. Each stage produces multiple hypotheses which are re-ranked using spatial validation. We evaluate the Tag&Parse approach on a corpus of Robotic Spatial Commands as part of the SemEval Task6 exercise. Our system accuracy is 87.35% and 60.84% with and without spatial validation.