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The goal of this investigation is to narrow the gap between SRL results from gold parses and from au- tomatic parses. We aim to do this by jointly perform- ing ...
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Charles Sutton and Andrew McCallum. 2005. Joint Parsing and Semantic Role Labeling. In Proceedings of the Ninth Conference on Computational Natural Language ...
Joint models of syntactic and semantic parsing have the potential to improve performance on both tasks—but to date, the best results have been achieved with.
This paper jointly performs parsing and semantic role labeling, using a probabilistic SRL system to rerank the results of a ProbabilisticParser, ...
To do this, we jointly perform parsing and semantic role labeling, using a probabilistic SRL system to rerank the results of a probabilistic parser. Our current ...
To do this, we jointly perform parsing and semantic role labeling, using a probabilistic SRL system to rerank the results of a probabilistic parser. Our current ...
To do this, we jointly perform parsing and semantic role labeling, using a probabilistic SRL system to rerank the results of a probabilistic parser. Our current ...
Abstract: We propose a simple encoder-decoder model for joint learning of dependency parsing and semantic role labeling (SRL). Experiments on CoNLL-2009 ...
Nov 3, 2021 · Semantic role labeling (SRL), namely, semantic parsing, is a shallow semantic parsing task that aims to recognize the predicate-argument ...
A joint model using CCG is introduced, which is motivated by the close link between CCG syntax and semantics and is the first to substantially improve both ...