---
title: "Broad-Coverage Semantic Parsing as Transduction — Zhang 2019"
description: "Semantic parsing frameworks such as AMR, SDP and UCCA each come with their own… 2.3 points. 62 references, cited by 57 papers here."
authors: ["Sheng Zhang", "Xutai Ma", "Kevin Duh", "Benjamin Van Durme"]
year: 2019
venue: "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)"
source: "https://aclanthology.org/D19-1392/"
doi: "10.18653/v1/d19-1392"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/zhang-2019-broad-coverage-semantic-parsing-as/"
---
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# Broad-Coverage Semantic Parsing as Transduction

**Authors:** [Sheng Zhang](https://md.research.elamur.ai/free/en/authors/sheng-zhang/), [Xutai Ma](https://md.research.elamur.ai/free/en/authors/xutai-ma/), [Kevin Duh](https://md.research.elamur.ai/free/en/authors/kevin-duh/) and [Benjamin Van Durme](https://md.research.elamur.ai/free/en/authors/benjamin-van-durme/) · **Year:** 2019 · **Venue:** [Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/) ([EMNLP 2019](https://md.research.elamur.ai/free/en/venues/emnlp/2019/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/D19-1392/) · [PDF](https://aclanthology.org/D19-1392.pdf) · [DOI 10.18653/v1/d19-1392](https://doi.org/10.18653/v1/d19-1392) · [OpenAlex](https://openalex.org/W2970796523)

**Citations:** 67 citations (OpenAlex, 2026-10-14) · [57](https://md.research.elamur.ai/free/en/papers/zhang-2019-broad-coverage-semantic-parsing-as/cited-by/) in our library, of the 141,840 papers whose bibliographies we read

## Summary
Semantic parsing frameworks such as AMR, SDP and UCCA each come with their own formal assumptions, so a parser built for one usually cannot be reused for another. Systems for unanchored graphs like AMR also often depend on a pre-trained aligner. The authors treat all three tasks as one transduction problem. Each target graph is first rewritten, losslessly and reversibly, as a rooted tree (arborescence). Reentrant nodes are duplicated and given shared indices, some DM edges are reversed with an "-of" label, and UCCA pre-terminals are collapsed. An attention-based encoder-decoder then grows this tree step by step. At each step it generates a target node, points back to an earlier node as the source, and assigns the relation label. The model needs no aligner, no data augmentation and no multi-task data. It sets new state-of-the-art results on AMR and UCCA, comes close to the best specialized DM parser, and runs faster than its two-stage predecessor. This makes it a promising basis for cross-framework and cross-lingual parsing.

## Key points
- AMR (SMATCH F1): 77.0 on LDC2017T10 (AMR 2.0, +0.7 over the previous best) and 71.3 on LDC2014T12 (AMR 1.0, +1.1).
- UCCA English-Wiki v1.2: 76.6 labeled F1, 2.3 points above the best published result. Adding labels to non-terminal nodes raised the score from 75.7.
- SDP (DM): 92.2 in-domain (WSJ) and 87.1 out-of-domain (Brown corpus) labeled F1. Only Dozat and Manning (2018) score higher (93.7 / 88.9), and their parser works only for bi-lexical graphs.
- The parser processes 1076 tokens/sec versus 617 for Zhang et al. (2019), about 1.7x faster, because it no longer needs an MST step.
- Incremental decoding produces 8% fewer invalid AMR graphs (for example, nodes with duplicate ARG1 edges) than Zhang et al. (2019).

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

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- [Johns Hopkins University](https://md.research.elamur.ai/free/en/universities/johns-hopkins-university/) — University, Baltimore, United States · 187 works · 92,194 citations

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## Cite

Cite as: Sheng Zhang, Xutai Ma, Kevin Duh and Benjamin Van Durme. 2019. Broad-Coverage Semantic Parsing as Transduction. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{zhang2019broad,
  title = {{Broad-Coverage Semantic Parsing as Transduction}},
  author = {Sheng Zhang, Xutai Ma, Kevin Duh and Benjamin {Van Durme}},
  booktitle = {Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},
  year = {2019},
  doi = {10.18653/v1/d19-1392},
  url = {https://doi.org/10.18653/v1/d19-1392}
}
```

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*Updated 24 October 2026*