---
title: "Comparing Knowledge Sources for Nominal — Markert 2005"
description: "Markert and Nissim study where lexical knowledge for resolving full-noun anaphors should come from."
authors: ["Katja Markert", "Malvina Nissim"]
year: 2005
venue: "Computational Linguistics"
source: "https://aclanthology.org/J05-3004/"
doi: "10.1162/089120105774321064"
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/markert-2005-comparing-knowledge-sources-nominal-anaphora/"
---
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# Comparing Knowledge Sources for Nominal Anaphora Resolution

**Authors:** [Katja Markert](https://md.research.elamur.ai/free/en/authors/katja-markert/), [Malvina Nissim](https://md.research.elamur.ai/free/en/authors/malvina-nissim/) · **Year:** 2005 · **Venue:** Computational Linguistics · **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/J05-3004/) · [PDF](https://aclanthology.org/J05-3004.pdf) · [DOI 10.1162/089120105774321064](https://doi.org/10.1162/089120105774321064) · [OpenAlex](https://openalex.org/W2116475692)

**Citations:** 63 citations (openalex-snapshot · 2026-10-14) · [19](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
Markert and Nissim study where lexical knowledge for resolving full-noun anaphors should come from. They focus on antecedent selection for two phenomena: other-anaphora (e.g., "other repercussions" pointing back to "costs") and coreference of definite NPs introduced by "the". They compare two approaches. One follows hyponymy and synonymy links in the hand-built hierarchy WordNet 1.7.1. The other counts how often shallow lexico-syntactic patterns occur in a corpus, either the BNC or the Web. The Web had not been used for this task before. The patterns are queried at resolution time instead of being used to build a fixed ontology. Data come from WSJ (Penn Treebank) texts, among others. WordNet turns out to miss many needed links, especially for subjective or context-dependent relations, and this gap is worse for other-anaphora. The Web method beats WordNet on other-anaphora and roughly matches it on definite NP coreference, while doing better on some subsets. The BNC method lags behind because of data sparseness. The approach is cheap and needs no hand-modelled knowledge, so it suits languages that have large corpora but lack taxonomies.

## Key points
- Three knowledge sources are compared for antecedent selection: WordNet 1.7.1, pattern frequencies from the BNC, and pattern frequencies from the Web.
- For other-anaphora, the Web-based algorithm outperforms the WordNet-based one. For definite NP coreference, the two are comparable overall, but the Web method adds more beyond the string-matching baseline (StrSet v2n).
- The BNC-based method is the weakest in both case studies. Corpus size mattered more than corpus cleanliness.
- The paper cites earlier evidence of WordNet's knowledge gap. Harabagiu et al. (2001) attributed over 30% of missed coreference links to missing semantic information. Strube et al. (2002) reported an F-measure of 33.9% for definite NPs versus 82.8% for pronouns.
- In related work (Modjeska, Markert, and Nissim 2003), adding a Web-score feature to a naive Bayes other-anaphora resolver gave an 11.4-point gain over a WordNet-based feature.

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

## Cited by

Cited by

19 papers of our library cite it (of the 140673 whose bibliographies we read); 8 of them have a page here, 11 not yet.

- [Coreference Semantics from Web Features](https://md.research.elamur.ai/free/en/papers/bansal-2012-coreference-semantics-web-features/)
- [Collective Classification for Fine-grained Information Status](https://md.research.elamur.ai/free/en/papers/markert-2012-collective-classification-fine-grained-information/)
- [Semantic Class Induction and Coreference Resolution](https://md.research.elamur.ai/free/en/papers/ng-2007-semantic-class-induction-coreference-resolution/)
- [Supervised Noun Phrase Coreference Research: The First Fifteen Years](https://md.research.elamur.ai/free/en/papers/ng-2010-supervised-noun-phrase-coreference-research/)
- [Exploiting Semantic Role Labeling, WordNet and Wikipedia for Coreference Resolution](https://md.research.elamur.ai/free/en/papers/ponzetto-2006-exploiting-semantic-role-labeling-wordnet/)
- [Sense Anaphoric Pronouns: Am I One?](https://md.research.elamur.ai/free/en/papers/recasens-2016-sense-anaphoric-pronouns-am-i/)
- [Antecedent Selection Techniques for High-Recall Coreference Resolution](https://md.research.elamur.ai/free/en/papers/versley-2007-antecedent-selection-techniques-high-recall/)
- [UBIU: A Language-Independent System for Coreference Resolution](https://md.research.elamur.ai/free/en/papers/zhekova-2010-ubiu-language-independent-system-coreference/)

## Cite

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

```bibtex
@article{markert2005comparing,
  title = {{Comparing Knowledge Sources for Nominal Anaphora Resolution}},
  author = {Markert, Katja and Nissim, Malvina},
  journal = {Computational Linguistics},
  year = {2005},
  doi = {10.1162/089120105774321064},
  url = {https://doi.org/10.1162/089120105774321064}
}
```

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- [next → Dependency Treelet Translation: Syntactically Informed Phrasal SMT](https://md.research.elamur.ai/free/en/papers/quirk-2005-dependency-treelet-translation-syntactically-informed/)
- [↑ back to papers of 2005](https://md.research.elamur.ai/free/en/papers/2005/)

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