Frame-Semantic Parsing
Venue
Computational Linguistics, vol. 40:1 (2014), pp. 9-56
Publication Year
2014
Authors
Dipanjan Das, Desai Chen, André F. T. Martins, Nathan Schneider, Noah A. Smith
BibTeX
Abstract
Frame semantics (Fillmore 1982) is a linguistic theory that has been instantiated
for English in the FrameNet lexicon (Fillmore, Johnson, and Petruck 2003). We solve
the problem of frame-semantic parsing using a two-stage statistical model that
takes lexical targets (i.e., content words and phrases) in their sentential
contexts and predicts frame-semantic structures. Given a target in context, the
first stage disambiguates it to a semantic frame. This model employs latent
variables and semi-supervised learning to improve frame disambiguation for targets
unseen at training time. The second stage finds the target's locally expressed
semantic arguments. At inference time, a fast exact dual decomposition algorithm
collectively predicts all the arguments of a frame at once in order to respect
declaratively stated linguistic constraints, resulting in qualitatively better
structures than naïve local predictors. Both components are feature-based and
discriminatively trained on a small set of annotated frame-semantic parses. On the
SemEval 2007 benchmark dataset, the approach, along with a heuristic identifier of
frame-evoking targets, outperforms the prior state of the art by significant
margins. Additionally, we present experiments on the much larger FrameNet 1.5
dataset. We have released our frame-semantic parser as open-source software.
