---
title: "Antecedent Selection Techniques for — Versley 2007"
description: "The paper addresses coreferent bridging: definite noun phrases whose antecedent has a different lexical head (e.g., \"the manor\" referring back to \"the…"
authors: ["Yannick Versley"]
year: 2007
venue: "Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)"
source: "https://aclanthology.org/D07-1052/"
licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)"
licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/versley-2007-antecedent-selection-techniques-high-recall/"
---
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# Antecedent Selection Techniques for High-Recall Coreference Resolution

**Authors:** [Yannick Versley](https://md.research.elamur.ai/free/en/authors/yannick-versley/) · **Year:** 2007 · **Venue:** Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL) · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/)

**Links:** [Publisher's page](https://aclanthology.org/D07-1052/) · [PDF](https://aclanthology.org/D07-1052.pdf) · [OpenAlex](https://openalex.org/W2147762470)

**Citations:** 19 citations (openalex-snapshot · 2026-10-14) · [8](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
The paper addresses coreferent bridging: definite noun phrases whose antecedent has a different lexical head (e.g., "the manor" referring back to "the house"). These cases limit recall because surface matching cannot find them. Versley studies antecedent selection on its own, assuming discourse-new definites are already identified. This yields an upper bound useful for feature design. The evaluation uses open-domain German newspaper text and compares several information sources:
- hypernymy lookup in GermaNet
- Web-mined shallow patterns
- distributional similarity (Lin98, RFF)
- association measures (Padó and Lapata's semantic space, Garera and Yarowsky's TheY)

The paper also separates lexical relation types and argues that relation-free association measures need semantic filtering. Otherwise they pick up non-coreferent associations such as house–door. A new distance-bounded similarity method nearly matches the precision of pattern search and beats Gasperin and Vieira's global similar-word lists. GermaNet and the Web patterns remain the most precise sources, but combining them with similarity- and association-based resolution substantially raises recall with only a modest precision cost.

## Key points
- Combining GermaNet and the Web-pattern approach with distance-bounded Lin similarity and a list of the 25 most similar words raised recall from 62% to 68% with little precision loss. Adding Lin's measure and TheY pushed recall to 69.7%, but at a larger precision cost.
- The syntax-based distributional measures (Lin, 1998; Padó and Lapata, 2003) ranked candidates better than Garera and Yarowsky's TheY association measure, possibly because TheY suffers from sparse data or noise.
- A hypothetical resolver combining these sources with perfect discourse-new detection would reach 88% precision and 83% recall on full NPs. This compares with 62% precision and 70% recall reported by Versley (2006) on the same data.
- In preliminary full-system experiments, adding pattern-based information increased overall recall by 0.6%, which corresponds to 46% more resolved coreferent bridging cases. Distributional similarity gave no noticeable gain over GermaNet alone.
- Sources covering different relations combine best, for example GermaNet for synonymy and hypernymy alongside patterns for instance relations. Precision matters especially when antecedent selection is integrated with discourse-new detection.

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

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/en/shelves/linguistics/)

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

## Cited by

Cited by

8 papers of our library cite it (of the 140673 whose bibliographies we read); 4 of them have a page here, 4 not yet.

- [Exploiting Zero Pronouns to Improve Chinese Coreference Resolution](https://md.research.elamur.ai/free/en/papers/kong-2013-exploiting-zero-pronouns-improve-chinese/)
- [Supervised Noun Phrase Coreference Research: The First Fifteen Years](https://md.research.elamur.ai/free/en/papers/ng-2010-supervised-noun-phrase-coreference-research/)
- [CoNLL-2011 Shared Task: Modeling Unrestricted Coreference in OntoNotes](https://md.research.elamur.ai/free/en/papers/pradhan-2011-conll-2011-shared-task-modeling/)
- [CoNLL-2012 Shared Task: Modeling Multilingual Unrestricted Coreference in OntoNotes](https://md.research.elamur.ai/free/en/papers/pradhan-2012-conll-2012-shared-task-modeling/)

## Cite

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

```bibtex
@inproceedings{versley2007antecedent,
  title = {{Antecedent Selection Techniques for High-Recall Coreference Resolution}},
  author = {Versley, Yannick},
  booktitle = {Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)},
  year = {2007},
  url = {https://aclanthology.org/D07-1052/}
}
```

- [← previous Annotating a Japanese Text Corpus with Predicate-Argument and Coreference Relations](https://md.research.elamur.ai/free/en/papers/iida-2007-annotating-japanese-text-corpus-predicate/)
- [next → Arabic Diacritization through Full Morphological Tagging](https://md.research.elamur.ai/free/en/papers/aclbulk-2007-habash-arabic-diacritization-through-full-morphological/)
- [↑ back to papers of 2007](https://md.research.elamur.ai/free/en/papers/2007/)

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