# An AMR Aligner Tuned by Transition-based Parser

Source: [An AMR Aligner Tuned by Transition-based Parser](<https://www.sota2.com/research/paper/68fa64e21e209131cea070a1>)

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

Data updated: 2025-12-25T02:36:51.380Z

Authors: Yijia Liu, Wanxiang Che, Bo Zheng, Bing Qin, Ting Liu

Published: 2018-10-08T16:00:50.000Z

## Abstract

In this paper, we propose a new rich resource enhanced AMR aligner which produces multiple alignments and a new transition system for AMR parsing along with its oracle parser. Our aligner is further tuned by our oracle parser via picking the alignment that leads to the highest-scored achievable AMR graph. Experimental results show that our aligner outperforms the rule-based aligner in previous work by achieving higher alignment F1 score and consistently improving two open-sourced AMR parsers. Based on our aligner and transition system, we develop a transition-based AMR parser that parses a sentence into its AMR graph directly. An ensemble of our parsers with only words and POS tags as input leads to 68.4 Smatch F1 score.

## 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 LDC2014T12 Newswire section](<https://www.sota2.com/research/sota/amr-parsing-on-ldc2014t12-newswire-section.md>): AMR parsing; LDC2014T12 Newswire section; F1 Score: 73.3.

- [AMR Parsing on LDC2014T12 (Full)](<https://www.sota2.com/research/sota/amr-parsing-on-ldc2014t12-full.md>): AMR parsing; LDC2014T12 (Full); F1 Score: 68.4.

- [Inter-lingual Subgraph Identification on ISI German](<https://www.sota2.com/research/sota/inter-lingual-subgraph-identification-on-isi-german.md>): Inter-lingual Subgraph Identification; ISI German; Precision: 73.7.

- [Inter-lingual Subgraph Identification on ISI Spanish (ES)](<https://www.sota2.com/research/sota/inter-lingual-subgraph-identification-on-isi-spanish-es.md>): Inter-lingual Subgraph Identification; ISI Spanish (ES); Precision: 84.

- [Inter-lingual Subgraph Identification on ISI Italian (IT)](<https://www.sota2.com/research/sota/inter-lingual-subgraph-identification-on-isi-italian-it.md>): Inter-lingual Subgraph Identification; ISI Italian (IT); Precision: 64.3.

- [Inter-lingual Subgraph Identification on ISI English](<https://www.sota2.com/research/sota/inter-lingual-subgraph-identification-on-isi-english.md>): Inter-lingual Subgraph Identification; ISI English; Precision: 92.1.

- [Subgraph Alignment on LEAMR 1.0 (test)](<https://www.sota2.com/research/sota/subgraph-alignment-on-leamr-1-0-test.md>): Subgraph Alignment; LEAMR 1.0 (test); Exact Alignment Precision: 85.68.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1810.03541>)

[PDF](<https://arxiv.org/pdf/1810.03541.pdf>)

[Implementation](<https://github.com/Oneplus/tamr>)