A Unified Bayesian Model of Scripts, Frames and Language
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Francis Ferraro and Benjamin Van Durme, A Unified Bayesian Model of Scripts, Frames and Language, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016.
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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 Fill-more'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 Fill-more'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.