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doi: 10.18653/v1/d19-1058
handle: 11573/1316550
We present VerbAtlas, a new, hand-crafted lexical-semantic resource whose goal is to bring together all verbal synsets from WordNet into semantically-coherent frames. The frames define a common, prototypical argument structure while at the same time providing new concept-specific information. In contrast to PropBank, which defines enumerative semantic roles, VerbAtlas comes with an explicit, cross-frame set of semantic roles linked to selectional preferences expressed in terms of WordNet synsets, and is the first resource enriched with semantic information about implicit, shadow, and default arguments. We demonstrate the effectiveness of VerbAtlas in the task of dependency-based Semantic Role Labeling and show how its integration into a high-performance system leads to improvements on both the in-domain and out-of-domain test sets of CoNLL-2009. VerbAtlas is available at http://verbatlas.org.
semantic role labeling; computational linguistics; natural language processing; neural network; argument structure; semantic clustering; bilstm; thematic roles;, strategies, tools, standards for lexicographic resources (objective 3), WP3
semantic role labeling; computational linguistics; natural language processing; neural network; argument structure; semantic clustering; bilstm; thematic roles;, strategies, tools, standards for lexicographic resources (objective 3), WP3
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