A Unified Bayesian Model of Scripts, Frames and Language

Authors

  • Francis Ferraro Johns Hopkins University
  • Benjamin Van Durme Johns Hopkins University

DOI:

https://doi.org/10.1609/aaai.v30i1.10328

Keywords:

semantic frames, natural language understanding, event semantics

Abstract

We present the first probabilistic model to capture all levels of the Minsky Frame structure, with the goal of corpus-based induction of scenario definitions. Our model unifies prior efforts in discourse-level modeling with that of Fillmore's related notion of frame, as captured in sentence-level, FrameNet semantic parses; as part of this, we resurrect the coupling among Minsky's frames, Schank's scripts and Fillmore's frames, as originally laid out by those authors. Empirically, our approach yields improved scenario representations, reflected quantitatively in lower surprisal and more coherent latent scenarios.

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Published

2016-03-05

How to Cite

Ferraro, F., & Van Durme, B. (2016). A Unified Bayesian Model of Scripts, Frames and Language. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1). https://doi.org/10.1609/aaai.v30i1.10328

Issue

Section

Technical Papers: NLP and Knowledge Representation