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# Transition-Based Dependency Parsing with Stack Long Short-Term Memory

**Authors:** [Chris Dyer](https://md.mova.elamur.ai/free/en/docs/papers/authors/chris-dyer/), Miguel Ballesteros, Wang Ling, Austin Matthews, [Noah A. Smith](https://md.mova.elamur.ai/free/en/docs/papers/authors/noah-a-smith/) · **Year:** 2015 · **Venue:** Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) **Link:** [aclanthology.org/P15-1033](https://aclanthology.org/P15-1033/) · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) — summary only

[**567** citations](https://openalex.org/works?filter=cites:W2134036914) openalex · 2026-10-19[**304** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/missing-2015-dyer-transition-based-dependency-parsing-stack/) of the 140673 papers whose bibliographies we read[Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)](https://aclanthology.org/volumes/P15-1/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/)

- [Publisher's page](https://aclanthology.org/P15-1033/)
- [PDF](https://aclanthology.org/P15-1033.pdf)
- [DOI 10.3115/v1/p15-1033](https://doi.org/10.3115/v1/p15-1033)
- [arXiv 1505.08075](https://arxiv.org/abs/1505.08075)
- [OpenAlex](https://openalex.org/W2134036914)

**Authors (5)**

1. [Chris Dyer](https://openalex.org/A5111222692) [Semantic Scholar](https://www.semanticscholar.org/author/1745899) · h 76 · 37927 citations · 275 works
2. [Miguel Ballesteros](https://openalex.org/A5101731788) [ORCID](https://orcid.org/0000-0003-3949-0361) · [Semantic Scholar](https://www.semanticscholar.org/author/143668305) · h 32 · 9201 citations · 137 works
3. Wang Ling [Semantic Scholar](https://www.semanticscholar.org/author/1379953252)
4. [Austin Matthews](https://openalex.org/A5066163749) [Semantic Scholar](https://www.semanticscholar.org/author/144633696) · h 7 · 1458 citations · 12 works
5. [Noah A. Smith](https://openalex.org/A5088517824) [ORCID](https://orcid.org/0000-0002-2310-6380) · [Semantic Scholar](https://www.semanticscholar.org/author/144365875) · h 94 · 40232 citations · 486 works

Citations and author metrics from openalex (2026-10-19); authors with the same name are not always told apart.

## What it is about

The paper introduces the stack LSTM: an LSTM with a stack pointer, so that pushes and pops take constant time and the network keeps a vector summary of the current stack contents. The arc-standard parser keeps three such stacks, for the buffer, for the partial trees (which are composed by a recursive network) and for the action history, so the classifier sees the whole parser state rather than a few words near the top. The model is trained by backpropagation through the whole parse. On the English Penn Treebank with Stanford dependencies it reaches 93.1 UAS and 90.9 LAS on the test set, against 91.8 and 89.6 for the Chen and Manning parser. On Chinese (CTB5) it reaches 87.2 UAS and 85.7 LAS. Ablations show that predicted POS tags add little, and that composed representations of tree fragments beat representations of head words alone (92.2 UAS without composition, against 93.1 with it).

## Ideas

- I1. en/src/parse.rs: add perceptron features over the last three transitions and the stack summary of the head word, then measure LAS on EWT dev through `en parse-eval`, together with tokens per second on CPU, since speed is a Mova requirement.
- I2. en/src/parse.rs: add features for the leftmost and rightmost dependents of the top two stack items (a composed view of partial trees, instead of head words alone) and measure LAS on EWT dev against the current templates.
- I3. en parse-eval: run EWT dev with gold tags and with ptag tags, and report the LAS gap; the paper's POS ablation suggests the gap is small, which would let tagging run after parsing and save time.

## For Mova

The ideas touch the feature templates of `en/src/parse.rs` and the tag input from `en/src/ptag.rs`. The chapters are `languages/en/20-syntax-overview`, `languages/en/21-clause-structure` and `languages/en/24-coordination-subordination`, where the parser state matters most. Measure first I3, a single run on the existing parser, which says whether tags are worth their cost before any new feature is added.

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

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.3115/v1/p15-1033](https://doi.org/10.3115/v1/p15-1033) · [arXiv 1505.08075](https://arxiv.org/abs/1505.08075)

```
@inproceedings{dyer2015transition,
  title = {{Transition-Based Dependency Parsing with Stack Long Short-Term Memory}},
  author = {Dyer, Chris and Ballesteros, Miguel and Ling, Wang and Matthews, Austin and Smith, Noah A.},
  booktitle = {Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},
  year = {2015},
  doi = {10.3115/v1/p15-1033},
  eprint = {1505.08075},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.3115/v1/p15-1033}
}
```

- [← previous A Fast and Accurate Dependency Parser using Neural Networks](https://md.mova.elamur.ai/free/en/docs/papers/missing-2014-chen-fast-accurate-dependency-parser-neural/)
- [next → An Improved Non-monotonic Transition System for Dependency Parsing](https://md.mova.elamur.ai/free/en/docs/papers/missing-2015-honnibal-improved-non-monotonic-transition-system/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

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