Parsing Natural Language Conversations using Contextual Cues

Shashank Srivastava, Amos Azaria, Tom Mitchell
2017 Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence  
In this work, we focus on semantic parsing of natural language conversations. Most existing methods for semantic parsing are based on understanding the semantics of a single sentence at a time. However, understanding conversations also requires an understanding of conversational context and discourse structure across sentences. We formulate semantic parsing of conversations as a structured prediction task, incorporating structural features that model the 'flow of discourse' across sequences of
more » ... cross sequences of utterances. We create a dataset for semantic parsing of conversations, consisting of 113 real-life sequences of interactions of human users with an automated email assistant. The data contains 4759 natural language statements paired with annotated logical forms. Our approach yields significant gains in performance over traditional semantic parsing.
doi:10.24963/ijcai.2017/571 dblp:conf/ijcai/SrivastavaAM17 fatcat:othzbjb3sneabi2dvectasym2q