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# Antecedent Selection for Sluicing: Structure and Content

**Authors:** [Pranav Anand](https://md.mova.elamur.ai/free/en/docs/papers/authors/pranav-anand/) and [Daniel Hardt](https://md.mova.elamur.ai/free/en/docs/papers/authors/daniel-hardt/) · **Year:** 2016 · **Venue:** Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP 2016) **Link:** [aclanthology.org/D16-1131](https://aclanthology.org/D16-1131/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**10** citations](https://openalex.org/works?filter=cites:W2567206440) openalex · 2026-10-19[**7** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2016-anand-antecedent-selection-sluicing-structure-content/) of the 140673 papers whose bibliographies we read[Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing](https://aclanthology.org/volumes/D16-1/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/D16-1131/)
- [PDF](https://aclanthology.org/D16-1131.pdf)
- [DOI 10.18653/v1/d16-1131](https://doi.org/10.18653/v1/d16-1131)
- [OpenAlex](https://openalex.org/W2567206440)

**Authors (2)**

1. [Pranav Anand](https://openalex.org/A5058849628) [Semantic Scholar](https://www.semanticscholar.org/author/49936558) · h 19 · 2232 citations · 83 works
2. [Daniel Hardt](https://openalex.org/A5054824570) [ORCID](https://orcid.org/0000-0001-6041-1475) · [Semantic Scholar](https://www.semanticscholar.org/author/144610213) · h 19 · 1785 citations · 101 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 asks which earlier sentence or clause a sluice refers to. It argues that both syntax and discourse matter, and it builds features for the structural relation between the sluice and each candidate, for discourse relations, and for the match between the candidate's content and the wh-type of the sluice. A linear model is trained with hill-climbing on the 4,100 sluices from the New York Times in the Anand and McCloskey (2015) data. The development set has 453 sluices from 1994–95, and the test set 1,732 from 1996–2000, with 10-fold cross-validation. The model reaches 72.4% accuracy, well above strong hand-built baselines. Distance is the strongest single group: 63% of antecedents are in the same sentence as the sluice, and 33% in the sentence before.

## Ideas

- I1. `en/src/ctx.rs`: use the paper's distance feature as the first candidate ranking, since it carries most of the signal. Measure accuracy on a sluice test set whose licence allows testing, against a random candidate baseline.
- I2. wh-type check in `en/src/expert.rs`: a candidate must match the sluice's wh-type on the content it supplies (for example, "how much" needs a measure, "how" needs a manner clause). Report the error rate per wh-type, as the paper does by sluice type.
- I3. Model comparison on the same features: compare the hill-climbing model with the averaged perceptron of `en` on the development part only, with `en folds`. Keep the test set held out until the release check.

## For Mova

The code is `en/src/ctx.rs`, `en/src/expert.rs` and the perceptron in `en/src/parse.rs`. The chapter is [29. Ellipsis, word order and information structure](https://md.mova.elamur.ai/free/en/docs/languages/en/29-ellipsis-word-order-information-structure/). The sluice data is NC, so it is for tests only. Measure first: the distance-only ranking on any sluice set we may test on.

Topics: [Discourse analysis](https://md.mova.elamur.ai/free/en/docs/papers/topics/discourse-analysis/) · [Coreference resolution](https://md.mova.elamur.ai/free/en/docs/papers/topics/coreference-resolution/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.18653/v1/d16-1131](https://doi.org/10.18653/v1/d16-1131)

```
@inproceedings{anand2016antecedent,
  title = {{Antecedent Selection for Sluicing: Structure and Content}},
  author = {Anand, Pranav and Hardt, Daniel},
  booktitle = {Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing},
  year = {2016},
  doi = {10.18653/v1/d16-1131},
  url = {https://doi.org/10.18653/v1/d16-1131}
}
```

- [← previous A Hierarchy with, of, and for Preposition Supersenses](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2015-schneider-hierarchy-preposition-supersenses/)
- [next → Evaluating Inter-Annotator Agreement on Historical Spelling Normalization](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2016-bollmann-evaluating-inter-annotator-agreement-historical/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

## References

26 references, 4 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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