A synergetic semantic role labeling model with the introduction of fluctuating force accompanied with word sense information
Authors:
- 10 January 2017
- journal article
- Published by SAGE Publications in Intelligent Data Analysis: An International Journal
- Vol. 21 (1) , 5-18
Abstract
Semantic role labeling (SRL) is a key problem in natural language processing which goal is to find a sentence-level semantic representation. Word sense information plays an important role on the determination of semantic roles. The introduction of woKeywords
This publication has 28 references indexed in Scilit:
- Synergetic method of traffic state recognition based on manifold learning2009
- Joint learning of preposition senses and semantic roles of prepositional phrases2009
- The CoNLL-2009 shared task2009
- The Importance of Syntactic Parsing and Inference in Semantic Role LabelingComputational Linguistics, 2008
- A Global Joint Model for Semantic Role LabelingComputational Linguistics, 2008
- The CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies2008
- Word-sense disambiguation for machine translation2005
- Question answering based on semantic structures2004
- Using predicate-argument structures for information extraction2003
- Synergetic Computers and Cognition1991