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# We Understand Elliptical Sentences, and Language Models should Too: A New Dataset for Studying Ellipsis and its Interaction with Thematic Fit

**Authors:** Davide Testa, [Emmanuele Chersoni](https://md.mova.elamur.ai/free/en/docs/papers/authors/emmanuele-chersoni/), [Alessandro Lenci](https://md.mova.elamur.ai/free/en/docs/papers/authors/alessandro-lenci/) · **Year:** 2023 · **Venue:** Proceedings of the 61st Annual Meeting of the ACL (Volume 1: Long Papers) **Link:** [aclanthology.org/2023.acl-long.188](https://aclanthology.org/2023.acl-long.188/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**3** citations](https://openalex.org/works?filter=cites:W4385571448) openalex · 2026-10-18[**5** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/acl-2023-testa-we-understand-elliptical-sentences-language/) of the 140673 papers whose bibliographies we read[Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)](https://aclanthology.org/volumes/2023.acl-long/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/2023.acl-long.188/)
- [PDF](https://aclanthology.org/2023.acl-long.188.pdf)
- [DOI 10.18653/v1/2023.acl-long.188](https://doi.org/10.18653/v1/2023.acl-long.188)
- [OpenAlex](https://openalex.org/W4385571448)

**Authors (3)**

1. [Davide Testa](https://openalex.org/A5088503816) [ORCID](https://orcid.org/0009-0002-2489-5323) · h 3 · 3205 citations · 11 works
2. [Emmanuele Chersoni](https://openalex.org/A5079921667) [ORCID](https://orcid.org/0000-0001-8742-0451) · h 16 · 873 citations · 114 works
3. [Alessandro Lenci](https://openalex.org/A5050795259) [ORCID](https://orcid.org/0000-0001-5790-4308) · h 31 · 5785 citations · 349 works

Citations and author metrics from openalex (2026-10-18); authors with the same name are not always told apart.

## What it is about

The authors build ELLie, a dataset of English elliptical sentences (sluicing, gapping and other constructions) organised by thematic role: agent, patient, instrument, location and time. Each item pairs a typical, atypical or impossible filler with the elided clause. They test two Transformer language models on three tasks: whether the sentence probability is higher for typical events, whether the probability of candidate fillers follows thematic fit, and whether the models can retrieve the elided verb. The models prefer typical events, but they fail to separate atypical from impossible ones and retrieve the elided verb poorly. The authors conclude that the models have limited knowledge of ellipsis.

## Ideas

- I1. `prag` and `world`: recover the elided predicate by copying the frame of the antecedent clause, and measure the share of ELLie elided verbs that are recovered (test only).
- I2. `en/src/parse.rs` on the elliptical clauses: UAS and LAS of `en` on the ELLie sentences, to see whether the parser attaches the remnant to the right head (test only).
- I3. A thematic-fit score in `world` from counts over the school corpus (no foreign language model), measured by the accuracy of separating typical from atypical items in ELLie Task 1 (test only).

## For Mova

Ellipsis is a case where the tree alone does not give the meaning, which is the point of `prag`. The language models are not allowed in Mova, so only the count-based fit and the frame-copy rule are options. Relevant chapters are `languages/en/29-ellipsis-word-order-information-structure` and `23-complementation`. Measure first the share of ELLie elided verbs recovered by the frame copy, with no training on the dataset.

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.18653/v1/2023.acl-long.188](https://doi.org/10.18653/v1/2023.acl-long.188)

```
@inproceedings{testa2023we,
  title = {{We Understand Elliptical Sentences, and Language Models should Too: A New Dataset for Studying Ellipsis and its Interaction with Thematic Fit}},
  author = {Testa, Davide and Chersoni, Emmanuele and Lenci, Alessandro},
  booktitle = {Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2023},
  doi = {10.18653/v1/2023.acl-long.188},
  url = {https://doi.org/10.18653/v1/2023.acl-long.188}
}
```

- [← previous Hexatagging: Projective Dependency Parsing as Tagging](https://md.mova.elamur.ai/free/en/docs/papers/acl-2023-amini-hexatagging-projective-dependency-parsing-as/)
- [next → Tokenization as the Initial Phase in NLP](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-1992-webster-tokenization-as-initial-phase-nlp/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

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