Year: 2014
Type: conference-paper
Abstract: We present a novel technique for semantic frame identification using distributed representations of predicates and their syntactic context; this technique leverages automatic syntactic parses and a generic set of word embeddings.Given labeled data annotated with frame-semantic parses, we learn a model that projects the set of word representations for the syntactic context around a predicate to a low dimensional representation.The latter is used for semantic frame identification; with a standard argument identification method inspired by prior work, we achieve state-ofthe-art results on FrameNet-style framesemantic analysis.Additionally, we report strong results on PropBank-style semantic role labeling in comparison to prior work.* The majority of this research was carried out during an internship at Google.
DOI: 10.3115/v1/p14-1136
Institutions: University of Oxford, Google (United States)
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2168963845