Paper: Understanding Mental States in Natural Language

ACL ID W09-3708
Title Understanding Mental States in Natural Language
Venue International Conference on Computational Semantics
Session Main Conference
Year 2009
Authors
  • Wei Chen (Carnegie Mellon University, Pittsburgh PA)

Understanding mental states in narratives is an important aspect of human language comprehension. By “mental states” we refer to beliefs, states of knowledge, points of view, and suppositions, all of which may change over time. In this paper, we propose an approach for automatically extracting and understanding multiple mental states in stories. Our model consists of two parts: (1) a parser that takes an English sentence and translates it to some semantic operations; (2) a mental-state inference engine that reads in the semantic operations and produces a situation model that represents the meaning of the sentence. We present the performance of the system on a corpus of children stories containing both fictional and non-fictional texts.