---
title: "Learning to Resolve Bridging References — Poesio 2004"
description: "The paper addresses mereological bridging references in English: definite noun phrases such as \"the top\" that refer to a part of an entity mentioned…"
authors: ["Massimo Poesio", "Rahul Mehta", "Axel Maroudas", "Janet Hitzeman"]
year: 2004
venue: "Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04)"
source: "https://aclanthology.org/P04-1019/"
doi: "10.3115/1218955.1218974"
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/papers/poesio-2004-learning-resolve-bridging-references/"
---
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# Learning to Resolve Bridging References

**Authors:** [Massimo Poesio](https://md.research.elamur.ai/free/authors/massimo-poesio/), Rahul Mehta, Axel Maroudas, Janet Hitzeman · **Year:** 2004 · **Venue:** Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04) · **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/P04-1019/) · [PDF](https://aclanthology.org/P04-1019.pdf) · [DOI 10.3115/1218955.1218974](https://doi.org/10.3115/1218955.1218974) · [OpenAlex](https://openalex.org/W2171549925)

**Citations:** 98 citations (openalex-snapshot · 2026-10-14) · [46](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
The paper addresses mereological bridging references in English: definite noun phrases such as "the top" that refer to a part of an entity mentioned earlier. Earlier work had tested two kinds of evidence separately. Salience cues, such as choosing the first-mentioned entity of the previous sentence, and lexical relatedness, measured with WordNet, vector lexicons or construction patterns, each stayed below roughly 40% accuracy. The authors combine both kinds of evidence by treating anchor identification as a binary classification task over candidate antecedents. The features are first mention, utterance distance, and a lexical distance score computed either from Google hit counts or from WordNet, where hypernym paths compensate for missing meronymy links. They train their own MLP, plus Weka's neural network and Naive Bayes, on the GNOME corpus. The combined features clearly beat all baselines and previously published results. WordNet distance performs about as well as Google, and slightly better for definite descriptions. This shows that pairing salience with lexical knowledge is effective, and that WordNet can still be useful for part-of bridging.

## Key points
- Data: 58 mereological bridging descriptions from the GNOME corpus. A second experiment adds all bridging references, including indefinite NPs, for 153 positive instances.
- On balanced data, the authors' MLP reaches 79.3% correct with WN distance and 76.7% with Google distance. The F-values for positive instances are 79.6% (WN) and 77.6% (Google).
- On the extended set of all mereological references, the F-measure is 76.3% with WN and 75.8% with Google, so the two resources perform essentially the same.
- In a harder test, classifiers pick anchors from all 346 candidate antecedents in context. The best result, F=.5, combines Google and WN distance with a larger, unbalanced training set. This is about 66% above the strongest baseline (first mention only).
- Planned work: enlarge the dataset, integrate the method into the GUITAR anaphora resolution system, and detect bridging descriptions automatically.

*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/shelves/linguistics/)

Topics: [Coreference resolution](https://md.research.elamur.ai/free/topics/coreference-resolution/)

## Cited by

Cited by

46 papers of our library cite it (of the 140673 whose bibliographies we read); 27 of them have a page here, 19 not yet.

- [Coreference Semantics from Web Features](https://md.research.elamur.ai/free/papers/bansal-2012-coreference-semantics-web-features/)
- [Annotating Bridging Anaphors in Italian: in Search of Reliability](https://md.research.elamur.ai/free/papers/caselli-2006-annotating-bridging-anaphors-italian-search/)
- [Experiments on bridging across languages and genres](https://md.research.elamur.ai/free/papers/grishina-2016-experiments-bridging-across-languages-genres/)
- [Cascading Collective Classification for Bridging Anaphora Recognition using a Rich Linguistic Feature Set](https://md.research.elamur.ai/free/papers/hou-2013-cascading-collective-classification-bridging-anaphora/)
- [Global Inference for Bridging Anaphora Resolution](https://md.research.elamur.ai/free/papers/hou-2013-global-inference-bridging-anaphora-resolution/)
- [A Rule-Based System for Unrestricted Bridging Resolution: Recognizing Bridging Anaphora and Finding Links to Antecedents](https://md.research.elamur.ai/free/papers/hou-2014-rule-based-system-unrestricted-bridging/)
- [A Deterministic Algorithm for Bridging Anaphora Resolution](https://md.research.elamur.ai/free/papers/hou-2018-deterministic-algorithm-bridging-anaphora-resolution/)
- [Enhanced Word Representations for Bridging Anaphora Resolution](https://md.research.elamur.ai/free/papers/hou-2018-enhanced-word-representations-bridging-anaphora/)
- [Unrestricted Bridging Resolution](https://md.research.elamur.ai/free/papers/hou-2018-unrestricted-bridging-resolution/)
- [Bridging Anaphora Resolution as Question Answering](https://md.research.elamur.ai/free/papers/hou-2020-bridging-anaphora-resolution-as-question/)
- [Annotating a Japanese Text Corpus with Predicate-Argument and Coreference Relations](https://md.research.elamur.ai/free/papers/iida-2007-annotating-japanese-text-corpus-predicate/)
- [Bridging Resolution: A Survey of the State of the Art](https://md.research.elamur.ai/free/papers/kobayashi-2020-bridging-resolution-survey-state-art/)
- [Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules](https://md.research.elamur.ai/free/papers/lee-2013-deterministic-coreference-resolution-based-entity/)
- [Comparing Knowledge Sources for Nominal Anaphora Resolution](https://md.research.elamur.ai/free/papers/markert-2005-comparing-knowledge-sources-nominal-anaphora/)
- [Collective Classification for Fine-grained Information Status](https://md.research.elamur.ai/free/papers/markert-2012-collective-classification-fine-grained-information/)
- [Semantic Class Induction and Coreference Resolution](https://md.research.elamur.ai/free/papers/ng-2007-semantic-class-induction-coreference-resolution/)
- [Supervised Noun Phrase Coreference Research: The First Fifteen Years](https://md.research.elamur.ai/free/papers/ng-2010-supervised-noun-phrase-coreference-research/)
- [Introducing the Prague Discourse Treebank 1.0](https://md.research.elamur.ai/free/papers/polakova-2013-introducing-prague-discourse-treebank-1/)
- [Resolving Complex Cases of Definite Pronouns: The Winograd Schema Challenge](https://md.research.elamur.ai/free/papers/rahman-2012-resolving-complex-cases-definite-pronouns/)
- [Bridging resolution: Task definition, corpus resources and rule-based experiments](https://md.research.elamur.ai/free/papers/roesiger-2018-bridging-resolution-task-definition-corpus/)
- [Rule- and Learning-based Methods for Bridging Resolution in the ARRAU Corpus](https://md.research.elamur.ai/free/papers/roesiger-2018-rule-learning-based-methods-bridging/)
- [Bridging Corpus for Russian in comparison with Czech](https://md.research.elamur.ai/free/papers/roitberg-2016-bridging-corpus-russian-comparison-czech/)
- [BASHI: A Corpus of Wall Street Journal Articles Annotated with Bridging Links](https://md.research.elamur.ai/free/papers/rosiger-2018-bashi-corpus-wall-street-journal/)
- [A Probabilistic Model for Associative Anaphora Resolution](https://md.research.elamur.ai/free/papers/sasano-2009-probabilistic-model-associative-anaphora-resolution/)
- [Improving Pronoun Resolution Using Statistics-Based Semantic Compatibility Information](https://md.research.elamur.ai/free/papers/yang-2005-improving-pronoun-resolution-statistics-based/)
- [Coreference Resolution Using Semantic Relatedness Information from Automatically Discovered Patterns](https://md.research.elamur.ai/free/papers/yang-2007-coreference-resolution-semantic-relatedness-information/)
- [Multitask Learning-Based Neural Bridging Reference Resolution](https://md.research.elamur.ai/free/papers/yu-2020-multitask-learning-based-neural-bridging/)

## Cite

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

```bibtex
@inproceedings{poesio2004learning,
  title = {{Learning to Resolve Bridging References}},
  author = {Poesio, Massimo and Mehta, Rahul and Maroudas, Axel and Hitzeman, Janet},
  booktitle = {Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04)},
  year = {2004},
  doi = {10.3115/1218955.1218974},
  url = {https://doi.org/10.3115/1218955.1218974}
}
```

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