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# Integrating Graph-Based and Transition-Based Dependency Parsers in the Deep Contextualized Era

**Authors:** [Agnieszka Falenska](https://md.mova.elamur.ai/free/en/docs/papers/authors/agnieszka-falenska/), [Anders Björkelund](https://md.mova.elamur.ai/free/en/docs/papers/authors/anders-bjorkelund/) and [Jonas Kuhn](https://md.mova.elamur.ai/free/en/docs/papers/authors/jonas-kuhn/) · **Year:** 2020 · **Venue:** Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies **Link:** [aclanthology.org/2020.iwpt-1.4](https://aclanthology.org/2020.iwpt-1.4/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**3** citations](https://openalex.org/works?filter=cites:W3037311427) openalex-snapshot · 2026-10-14[**5** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/ud-2020-falenska-integrating-graph-based-transition-based/) of the 140673 papers whose bibliographies we read[Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies](https://aclanthology.org/volumes/2020.iwpt-1/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/2020.iwpt-1.4/)
- [PDF](https://aclanthology.org/2020.iwpt-1.4.pdf)
- [DOI 10.18653/v1/2020.iwpt-1.4](https://doi.org/10.18653/v1/2020.iwpt-1.4)
- [OpenAlex](https://openalex.org/W3037311427)

**Authors (3)**

1. [Agnieszka Falenska](https://openalex.org/A5037220308) [ORCID](https://orcid.org/0009-0008-3003-9658) · [Semantic Scholar](https://www.semanticscholar.org/author/3443367) · h 8 · 166 citations · 44 works
2. [Anders Björkelund](https://openalex.org/A5017258586) [ORCID](https://orcid.org/0000-0001-7426-914X) · [Semantic Scholar](https://www.semanticscholar.org/author/1737207) · h 17 · 1205 citations · 46 works
3. [Jonas Kuhn](https://openalex.org/A5101531241) [ORCID](https://orcid.org/0000-0003-2860-5960) · [Semantic Scholar](https://www.semanticscholar.org/author/1716963) · h 22 · 1543 citations · 160 works

Citations and author metrics from openalex-snapshot (2026-10-14); authors with the same name are not always told apart.

## What it is about

The paper asks whether combining a graph-based and a transition-based parser still helps once the parsers use BiLSTM encoders and ELMo embeddings. The authors re-implement the Kiperwasser and Goldberg architectures and test two combination methods, blending (arc voting followed by a maximum spanning tree) and feature-based stacking, on several UD treebanks, with LAS on the test sets averaged over six seeds. Their finding is that the remaining diversity between the two models is below the level of two models trained with different seeds, so integration no longer raises accuracy. When both parsers use BiLSTMs, the graph-based one is consistently better, because its globally trained BiLSTM states carry more look-ahead syntactic information. Multi-task learning from the graph-based parser helps the transition-based parser, most of all on treebanks with many right-headed dependencies.

## Ideas

- I1. Seed-spread baseline for `en`: train the perceptron parser (`en/src/parse.rs`, beam 8) with six shuffle seeds and report the spread of EWT test LAS; an ensemble counts as a gain only if it clears that spread, as the paper argues.
- I2. Arc-voting blend of `en` and `gparse` (`gparse/src/eisner.rs` for decoding): combine the two arc score tables and decode the result; measure EWT test LAS and the spread over seeds, expecting little gain because both use the same lexical features.
- I3. Right-headed share per bank: report `en` and `gparse` LAS against the share of right-headed dependencies on each bank (GUM and ESLSpok are test only); if the graph-style model wins on right-headed banks, try an auxiliary arc-scoring loss in `gparse` and measure EWT dev LAS.

## For Mova

The parsers are `en/src/parse.rs` (transition, perceptron) and `gparse/src/eisner.rs` with the biaffine model (graph). The chapter is [20. Syntax: the Universal Dependencies frame](https://md.mova.elamur.ai/free/en/docs/languages/en/20-syntax-overview/). Measure first the seed spread on EWT test, once per release, since without it no ensemble gain can be claimed.

Topics: [Dependency parsing](https://md.mova.elamur.ai/free/en/docs/papers/topics/dependency-parsing/) · [Treebanks](https://md.mova.elamur.ai/free/en/docs/papers/topics/treebanks/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.18653/v1/2020.iwpt-1.4](https://doi.org/10.18653/v1/2020.iwpt-1.4)

```
@inproceedings{falenska2020integrating,
  title = {{Integrating Graph-Based and Transition-Based Dependency Parsers in the Deep Contextualized Era}},
  author = {Falenska, Agnieszka and Björkelund, Anders and Kuhn, Jonas},
  booktitle = {Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies},
  year = {2020},
  doi = {10.18653/v1/2020.iwpt-1.4},
  url = {https://doi.org/10.18653/v1/2020.iwpt-1.4}
}
```

- [← previous How Much of Enhanced UD Is Contained in UD?](https://md.mova.elamur.ai/free/en/docs/papers/ud-2020-ek-how-much-enhanced-ud-is/)
- [next → RobertNLP at the IWPT 2020 Shared Task: Surprisingly Simple Enhanced UD Parsing for English](https://md.mova.elamur.ai/free/en/docs/papers/ud-2020-grunewald-robertnlp-iwpt-2020-shared-task/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

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