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An Incremental Parser for Abstract Meaning Representation

2016-08-22EACL 2017Code Available1· sign in to hype

Marco Damonte, Shay B. Cohen, Giorgio Satta

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Abstract

Meaning Representation (AMR) is a semantic representation for natural language that embeds annotations related to traditional tasks such as named entity recognition, semantic role labeling, word sense disambiguation and co-reference resolution. We describe a transition-based parser for AMR that parses sentences left-to-right, in linear time. We further propose a test-suite that assesses specific subtasks that are helpful in comparing AMR parsers, and show that our parser is competitive with the state of the art on the LDC2015E86 dataset and that it outperforms state-of-the-art parsers for recovering named entities and handling polarity.

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Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
LDC2015E86AMREagerSmatch64Unverified

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