# An Incremental Parser for Abstract Meaning Representation

Source: [An Incremental Parser for Abstract Meaning Representation](<https://www.sota2.com/research/paper/68fa634e1e209131ce9fdf74>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-12-22T13:14:15.126Z

Authors: Marco Damonte, Shay B. Cohen, Giorgio Satta

Published: 2016-08-22T10:30:18.000Z

## 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [AMR Parsing on LDC2015E86 R1 (test)](<https://www.sota2.com/research/sota/amr-parsing-on-ldc2015e86-r1-test.md>): AMR parsing; LDC2015E86 R1 (test); Smatch: 64.

- [AMR Parsing on LDC2015E86 (test)](<https://www.sota2.com/research/sota/amr-parsing-on-ldc2015e86-test.md>): AMR parsing; LDC2015E86 (test); F1 Score: 64.

- [AMR Parsing on LDC2014T12 (Full)](<https://www.sota2.com/research/sota/amr-parsing-on-ldc2014t12-full.md>): AMR parsing; LDC2014T12 (Full); F1 Score: 66.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1608.06111>)

[PDF](<https://arxiv.org/pdf/1608.06111.pdf>)