---
title: "Cross-Document Coreference on a Large Scale — Gooi 2004"
description: "The paper addresses cross-document coreference: deciding whether identical person names in different documents refer to the same individual."
authors: ["Chung Heong Gooi", "James Allan"]
year: 2004
venue: "Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics: HLT-NAACL 2004"
source: "https://aclanthology.org/N04-1002/"
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/gooi-2004-cross-document-coreference-large-scale/"
---
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# Cross-Document Coreference on a Large Scale Corpus

**Authors:** Chung Heong Gooi, James Allan · **Year:** 2004 · **Venue:** Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics: HLT-NAACL 2004 · **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/N04-1002/) · [PDF](https://aclanthology.org/N04-1002.pdf) · [OpenAlex](https://openalex.org/W1502876877)

**Citations:** 119 citations (openalex-snapshot · 2026-10-14) · [26](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
The paper addresses cross-document coreference: deciding whether identical person names in different documents refer to the same individual. Earlier work was tested only on a small collection, so the authors built a much larger evaluation set, the "Person-x corpus". They drew documents from TREC volumes 1–3 using topic queries across 11 subject areas, tagged names with BBN's Identifinder, picked one person per document, and replaced that name with "person-x". The original names served as gold coreference chains. Each mention is represented by a 55-word context window (a "snippet"). Three ways of clustering snippets are compared: an incremental vector space approach approximating Bagga and Baldwin (1998), KL divergence, and agglomerative vector space. All are scored with B-CUBED. Agglomerative vector space gave the best F-measure on the original John Smith corpus and was far less sensitive to the choice of threshold. Its drawback is quadratic runtime. The study matters because it offers a scalable way to build test data and shows that results from small corpora may not carry over to large ones.

## Key points
- John Smith corpus: 197 New York Times articles mentioning 35 distinct John Smiths. Person-x corpus: 34,404 documents covering 14,767 real entities, roughly 46.7% of which appear only once.
- On John Smith, agglomerative vector space reached a peak F of 88.2%. The incremental method scored 84.3%, close to Bagga and Baldwin's 84.6%, and a single-link variant scored 81.4%.
- Evaluating separately within each genre lowered agglomerative F by 6 points to 77% and incremental F by about 5 points. KL divergence rose 3 points to 77%, matching agglomerative.
- A 55-word snippet window maximized F-measure on the John Smith corpus and was used in all experiments.
- Agglomerative clustering is O(n²) and took about 3× longer on Person-x. The authors consider this acceptable when the number of same-name mentions is small.

*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

26 papers of our library cite it (of the 140673 whose bibliographies we read); 5 of them have a page here, 21 not yet.

- [Who is Who and What is What: Experiments in Cross-Document Co-Reference](https://md.research.elamur.ai/free/papers/baron-2008-who-is-who-what-is/)
- [Cross-Document Co-Reference Resolution using Sample-Based Clustering with Knowledge Enrichment](https://md.research.elamur.ai/free/papers/dutta-2015-cross-document-co-reference-resolution/)
- [Streaming Cross Document Entity Coreference Resolution](https://md.research.elamur.ai/free/papers/rao-2010-streaming-cross-document-entity-coreference/)
- [Large-Scale Cross-Document Coreference Using Distributed Inference and Hierarchical Models](https://md.research.elamur.ai/free/papers/singh-2011-large-scale-cross-document-coreference/)
- [An NP-Cluster Based Approach to Coreference Resolution](https://md.research.elamur.ai/free/papers/yang-2004-np-cluster-based-approach-coreference/)

## Cite

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

```bibtex
@inproceedings{gooi2004cross,
  title = {{Cross-Document Coreference on a Large Scale Corpus}},
  author = {Gooi, Chung Heong and Allan, James},
  booktitle = {Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics: HLT-NAACL 2004},
  year = {2004},
  doi = {10.21236/ada458579},
  url = {https://doi.org/10.21236/ada458579}
}
```

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## References

10 references, 1 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Allan, James, ed. Topic Detection and Tracking: Event-based Information Organization, Kluwer Academic Publishers, 2002. [find](https://scholar.google.com/scholar?q=Allan%2C+James%2C+ed%2E+Topic+Detection+and+Tracking%3A+Event%2Dbased+Information+Organization%2C+Kluwer+Academic+Publishers%2C+2002%2E)
2. Allan, James and Raghavan, Hema. Entity Models: Construction and Application. Center for Intelligent Information Retrieval, Department of Computer Science, University of Massachusetts, 2002. [find](https://scholar.google.com/scholar?q=Allan%2C+James+and+Raghavan%2C+Hema%2E+Entity+Models%3A+Construction+and+Application%2E+Center+for+Intelligent+Information+Retrieval%2C+Department+of+Computer+Science%2C+University+of+Massachusetts%2C+2002%2E)
3. Bagga, Amit and Breck Baldwin. Algorithms for Scoring Coreference Chains. In Proceedings of the Linguistic Coreference Workshop at The First International Conference on Language Resources and Evaluation (LREC'98), pp563-566, 1998. [find](https://scholar.google.com/scholar?q=Bagga%2C+Amit+and+Breck+Baldwin%2E+Algorithms+for+Scoring+Coreference+Chains%2E+In+Proceedings+of+the+Linguistic+Coreference+Workshop+at+The+First+International+Conference+on+Language+Resources+and+Evaluati) [our card](https://md.research.elamur.ai/free/papers/bagga-1998-algorithms-scoring-coreference-chains/)
4. Bagga, Amit and Breck Baldwin. Entity-Based Cross-Document Coreferencing Using the Vector Space Model. Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and the 17th International Conference on Computational Linguistics (COLING-ACL'98),pp.79-85, 1998. [find](https://scholar.google.com/scholar?q=Bagga%2C+Amit+and+Breck+Baldwin%2E+Entity%2DBased+Cross%2DDocument+Coreferencing+Using+the+Vector+Space+Model%2E+Proceedings+of+the+36th+Annual+Meeting+of+the+Association+for+Computational+Linguistics+and+the+1)
5. Bagga, Amit and Breck Baldwin. Coreference as the Foundations for Link Analysis Over Free Text Databases. In Proceedings of the COLING-ACL'98 Content Visualization and Intermedia Representations Workshop (CVIR'98), pp. 19-24, 1998. [find](https://scholar.google.com/scholar?q=Bagga%2C+Amit+and+Breck+Baldwin%2E+Coreference+as+the+Foundations+for+Link+Analysis+Over+Free+Text+Databases%2E+In+Proceedings+of+the+COLING%2DACL%2798+Content+Visualization+and+Intermedia+Representations+Works)
6. Bagga, Amit, and Biermann, Alan. A Methodology for Cross-Document Coreference. In Proceedings of the Fifth Joint Conference on Information Sciences (JCIS 2000), pp. 207-210, 2000. [find](https://scholar.google.com/scholar?q=Bagga%2C+Amit%2C+and+Biermann%2C+Alan%2E+A+Methodology+for+Cross%2DDocument+Coreference%2E+In+Proceedings+of+the+Fifth+Joint+Conference+on+Information+Sciences+%28JCIS+2000%29%2C+pp%2E+207%2D210%2C+2000%2E)
7. Bagga, Amit and Baldwin, Breck. How Much Processing Is Required for Cross-Document Coreference? In Proceedings of the Linguistic Coreference Workshop (LREC'98), pp. 563-566, 1998. [find](https://scholar.google.com/scholar?q=Bagga%2C+Amit+and+Baldwin%2C+Breck%2E+How+Much+Processing+Is+Required+for+Cross%2DDocument+Coreference%3F+In+Proceedings+of+the+Linguistic+Coreference+Workshop+%28LREC%2798%29%2C+pp%2E+563%2D566%2C+1998%2E)
8. BBN Technologies. Rough ‘n’ Ready™: Audio Indexing for Meetings and News. [http://www.bbn.com/-speech/roughnready.html](http://www.bbn.com/-speech/roughnready.html) (2001) [↗](http://www.bbn.com/-speech/roughnready.html)
9. Kibble, Rodger and Kees, van Deemter. Coreference Annotation: Whither? Proceedings of LREC2000, Athens, pp. 1281-1286, 2000. [find](https://scholar.google.com/scholar?q=Kibble%2C+Rodger+and+Kees%2C+van+Deemter%2E+Coreference+Annotation%3A+Whither%3F+Proceedings+of+LREC2000%2C+Athens%2C+pp%2E+1281%2D1286%2C+2000%2E)
10. Lee, Lillian. On the Effectiveness of the Skew Divergence for Statistical Language Analysis, Technical Report, Department of Computer Science, Cornell University, 2001. [find](https://scholar.google.com/scholar?q=Lee%2C+Lillian%2E+On+the+Effectiveness+of+the+Skew+Divergence+for+Statistical+Language+Analysis%2C+Technical+Report%2C+Department+of+Computer+Science%2C+Cornell+University%2C+2001%2E)