2017
EACL
EACL 2017
Unsupervised AMR-Dependency Parse Alignment
Abstract
AbstractIn this paper, we introduce an Abstract Meaning Representation (AMR) to Dependency Parse aligner. Alignment is a preliminary step for AMR parsing, and our aligner improves current AMR parser performance. Our aligner involves several different features, including named entity tags and semantic role labels, and uses Expectation-Maximization training. Results show that our aligner reaches an 87.1% F-Score score with the experimental data, and enhances AMR parsing.
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Interdisciplinary Bridge
- Artificial Intelligence and Interdisciplinary and Knowledge & Reasoning and Natural Language Processing
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Keyword Pioneer
- amr parsing
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Hot Topic Early Bird
- semantic role labeling
Authors
Topics
Machine Learning > Learning Types > Unsupervised Learning
Natural Language Processing > Understanding > Parsing
Natural Language Processing > Understanding > Semantic Analysis
Natural Language Processing > Understanding > Syntax
Natural Language Processing > Resources & Methods > Text Representation
Knowledge & Reasoning > Representation > Knowledge Representation
Interdisciplinary > Linguistics > Computational Linguistics