---
title: "A Joint Model for Entity Analysis — Durrett 2014"
description: "Durrett and Klein address three closely linked parts of entity analysis that are usually solved separately or in a fixed pipeline: coreference…"
authors: ["Greg Durrett", "Dan Klein"]
year: 2014
venue: "Transactions of the Association for Computational Linguistics"
source: "https://aclanthology.org/Q14-1037/"
doi: "10.1162/tacl_a_00197"
licence: "CC BY 4.0 (ACL Anthology, TACL)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/papers/durrett-2014-joint-model-entity-analysis-coreference/"
---
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# A Joint Model for Entity Analysis: Coreference, Typing, and Linking

**Authors:** [Greg Durrett](https://md.research.elamur.ai/free/authors/greg-durrett/), [Dan Klein](https://md.research.elamur.ai/free/authors/dan-klein/) · **Year:** 2014 · **Venue:** Transactions of the Association for Computational Linguistics · **Licence:** [CC BY 4.0 (ACL Anthology, TACL)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/Q14-1037/) · [PDF](https://aclanthology.org/Q14-1037.pdf) · [DOI 10.1162/tacl\_a\_00197](https://doi.org/10.1162/tacl_a_00197) · [OpenAlex](https://openalex.org/W2293004735)

**Citations:** 234 citations (openalex-snapshot · 2026-10-14) · [95](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
Durrett and Klein address three closely linked parts of entity analysis that are usually solved separately or in a fixed pipeline: coreference resolution, coarse semantic typing (NER), and entity linking to Wikipedia. Their argument is that each task can fix the others' mistakes, so no pipeline order is ideal. For example, a nearby "the company" signals that "Dell" means the firm rather than the person.

They build a single structured conditional random field with one antecedent, type, and link variable per mention, plus latent Wikipedia query variables. Unary factors carry features from strong standalone baselines. Binary and ternary factors softly reward consistency across tasks, such as coreferent mentions sharing a type, and map NER types to Wikipedia infoboxes, categories, and article text. Exact inference is intractable, so they use belief propagation after pruning variable domains with a coarse model.

On ACE 2005 and OntoNotes, the joint model beats its independent baselines on every task and reaches state-of-the-art results. This shows that joint modeling can stay modular and efficient.

## Key points
- Evaluation covers two corpora with different mention standards and annotation layers: ACE 2005 and OntoNotes 5.0 (CoNLL 2011/2012 splits).
- On the OntoNotes / CoNLL 2011 test set, NER F1 reaches 84.04. This compares with 82.64 for the independent model (+1.40), 83.45 for the Illinois system, and 82.24 for Passos et al. (2014). The joint model has higher precision, while Illinois has higher recall.
- On ACE, entity linking matches Fahrni and Strube (2014). On OntoNotes, coreference is on par with Björkelund and Kuhn (2014), the best published system.
- Ablations show that removing any pairwise cross-task interaction hurts at least one task. The joint system runs only about twice as slow as the three separate models combined.
- The code is released as the Berkeley Entity Resolution System (nlp.cs.berkeley.edu). The paper appeared in TACL, vol. 2, 2014.

*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: [Named entity recognition](https://md.research.elamur.ai/free/topics/named-entity-recognition/) · [Coreference resolution](https://md.research.elamur.ai/free/topics/coreference-resolution/)

## Cited by

Cited by

95 papers of our library cite it (of the 140673 whose bibliographies we read); 19 of them have a page here, 76 not yet.

- [Named Entity Recognition with Bidirectional LSTM-CNNs](https://md.research.elamur.ai/free/papers/chiu-2015-named-entity-recognition-bidirectional-lstm/)
- [Entity-Centric Coreference Resolution with Model Stacking](https://md.research.elamur.ai/free/papers/clark-2015-entity-centric-coreference-resolution-model/)
- [Learning-Based Single-Document Summarization with Compression and Anaphoricity Constraints](https://md.research.elamur.ai/free/papers/durrett-2016-learning-based-single-document-summarization/)
- [Coreference in Wikipedia: Main Concept Resolution](https://md.research.elamur.ai/free/papers/ghaddar-2016-coreference-wikipedia-main-concept-resolution/)
- [Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers](https://md.research.elamur.ai/free/papers/guha-2015-removing-training-wheels-coreference-dataset/)
- [Neural Cross-Lingual Coreference Resolution And Its Application To Entity Linking](https://md.research.elamur.ai/free/papers/kundu-2018-neural-cross-lingual-coreference-resolution/)
- [A Joint Neural Model for Information Extraction with Global Features](https://md.research.elamur.ai/free/papers/lin-2020-joint-neural-model-information-extraction/)
- [Unsupervised Ranking Model for Entity Coreference Resolution](https://md.research.elamur.ai/free/papers/ma-2016-unsupervised-ranking-model-entity-coreference/)
- [Latent Structures for Coreference Resolution](https://md.research.elamur.ai/free/papers/martschat-2015-latent-structures-coreference-resolution/)
- [Projection-based Coreference Resolution Using Deep Syntax](https://md.research.elamur.ai/free/papers/novak-2017-projection-based-coreference-resolution-deep/)
- [A Joint Framework for Coreference Resolution and Mention Head Detection](https://md.research.elamur.ai/free/papers/peng-2015-joint-framework-coreference-resolution-mention/)
- [IMS HotCoref DE: A Data-driven Co-reference Resolver for German](https://md.research.elamur.ai/free/papers/roesiger-2016-ims-hotcoref-de-data-driven/)
- [Mind the GAP: A Balanced Corpus of Gendered Ambiguous Pronouns](https://md.research.elamur.ai/free/papers/webster-2018-mind-gap-balanced-corpus-gendered/)
- [Learning Anaphoricity and Antecedent Ranking Features for Coreference Resolution](https://md.research.elamur.ai/free/papers/wiseman-2015-learning-anaphoricity-antecedent-ranking-features/)
- [Learning Global Features for Coreference Resolution](https://md.research.elamur.ai/free/papers/wiseman-2016-learning-global-features-coreference-resolution/)
- [When Annotation Schemes Change Rules Help: A Configurable Approach to Coreference Resolution beyond OntoNotes](https://md.research.elamur.ai/free/papers/zeldes-2016-when-annotation-schemes-change-rules/)
- [Neural Coreference Resolution with Deep Biaffine Attention by Joint Mention Detection and Mention Clustering](https://md.research.elamur.ai/free/papers/zhang-2018-neural-coreference-resolution-deep-biaffine/)
- [Anatomy of OntoGUM—Adapting GUM to the OntoNotes Scheme to Evaluate Robustness of SOTA Coreference Algorithms](https://md.research.elamur.ai/free/papers/zhu-2021-anatomy-ontogum-adapting-gum-ontonotes/)
- [OntoGUM: Evaluating Contextualized SOTA Coreference Resolution on 12 More Genres](https://md.research.elamur.ai/free/papers/zhu-2021-ontogum-evaluating-contextualized-sota-coreference/)

## Cite

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

```bibtex
@article{durrett2014joint,
  title = {{A Joint Model for Entity Analysis: Coreference, Typing, and Linking}},
  author = {Durrett, Greg and Klein, Dan},
  journal = {Transactions of the Association for Computational Linguistics},
  year = {2014},
  doi = {10.1162/tacl\_a\_00197},
  url = {https://doi.org/10.1162/tacl_a_00197}
}
```

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## References

59 references, 31 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Amit Bagga and Breck Baldwin. 1998. Algorithms for Scoring Coreference Chains. In Proceedings of the Conference on Language Resources and Evaluation Workshop on Linguistics Coreference. [find](https://scholar.google.com/scholar?q=Amit+Bagga+and+Breck+Baldwin%2E+1998%2E+Algorithms+for+Scoring+Coreference+Chains%2E+In+Proceedings+of+the+Conference+on+Language+Resources+and+Evaluation+Workshop+on+Linguistics+Coreference%2E) [our card](https://md.research.elamur.ai/free/papers/bagga-1998-algorithms-scoring-coreference-chains/)
2. Mohit Bansal and Dan Klein. 2012. Coreference Semantics from Web Features. In Proceedings of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Mohit+Bansal+and+Dan+Klein%2E+2012%2E+Coreference+Semantics+from+Web+Features%2E+In+Proceedings+of+the+Association+for+Computational+Linguistics%2E) [our card](https://md.research.elamur.ai/free/papers/bansal-2012-coreference-semantics-web-features/)
3. Luisa Bentivogli, Pamela Forner, Claudio Giuliano, Alessandro Marchetti, Emanuele Pianta, and Kateryna Tymoshenko. 2010. [find](https://scholar.google.com/scholar?q=Luisa+Bentivogli%2C+Pamela+Forner%2C+Claudio+Giuliano%2C+Alessandro+Marchetti%2C+Emanuele+Pianta%2C+and+Kateryna+Tymoshenko%2E+2010%2E)
4. Extending English ACE 2005 Corpus Annotation with Ground-truth Links to Wikipedia. In Proceedings of the Workshop on The People’s Web Meets NLP: Collaboratively Constructed Semantic Resources. [find](https://scholar.google.com/scholar?q=Extending+English+ACE+2005+Corpus+Annotation+with+Ground%2Dtruth+Links+to+Wikipedia%2E+In+Proceedings+of+the+Workshop+on+The+People%E2%80%99s+Web+Meets+NLP%3A+Collaboratively+Constructed+Semantic+Resources%2E)
5. Anders Björkelund and Jonas Kuhn. 2014. Learning Structured Perceptrons for Coreference Resolution with Latent Antecedents and Non-local Features. In Proceedings of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Anders+Bjo%CC%88rkelund+and+Jonas+Kuhn%2E+2014%2E+Learning+Structured+Perceptrons+for+Coreference+Resolution+with+Latent+Antecedents+and+Non%2Dlocal+Features%2E+In+Proceedings+of+the+Association+for+Computational+) [our card](https://md.research.elamur.ai/free/papers/bjorkelund-2014-learning-structured-perceptrons-coreference-resolution/)
6. David Burkett and Dan Klein. 2012. Fast Inference in Phrase Extraction Models with Belief Propagation. In Proceedings of the North American Chapter of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=David+Burkett+and+Dan+Klein%2E+2012%2E+Fast+Inference+in+Phrase+Extraction+Models+with+Belief+Propagation%2E+In+Proceedings+of+the+North+American+Chapter+of+the+Association+for+Computational+Linguistics%2E)
7. Kai-Wei Chang, Rajhans Samdani, and Dan Roth. 2013. A Constrained Latent Variable Model for Coreference Resolution. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. [find](https://scholar.google.com/scholar?q=Kai%2DWei+Chang%2C+Rajhans+Samdani%2C+and+Dan+Roth%2E+2013%2E+A+Constrained+Latent+Variable+Model+for+Coreference+Resolution%2E+In+Proceedings+of+the+Conference+on+Empirical+Methods+in+Natural+Language+Processing) [our card](https://md.research.elamur.ai/free/papers/chang-2013-constrained-latent-variable-model-coreference/)
8. Xiao Cheng and Dan Roth. 2013. Relational Inference for Wikification. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. [find](https://scholar.google.com/scholar?q=Xiao+Cheng+and+Dan+Roth%2E+2013%2E+Relational+Inference+for+Wikification%2E+In+Proceedings+of+the+Conference+on+Empirical+Methods+in+Natural+Language+Processing%2E)
9. Silviu Cucerzan. 2007. Large-Scale Named Entity Disambiguation Based on Wikipedia Data. In Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). [find](https://scholar.google.com/scholar?q=Silviu+Cucerzan%2E+2007%2E+Large%2DScale+Named+Entity+Disambiguation+Based+on+Wikipedia+Data%2E+In+Proceedings+of+the+Joint+Conference+on+Empirical+Methods+in+Natural+Language+Processing+and+Computational+Nat)
10. Hal Daumé, III and Daniel Marcu. 2005. A Large-scale Exploration of Effective Global Features for a Joint Entity Detection and Tracking Model. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. [find](https://scholar.google.com/scholar?q=Hal+Daume%CC%81%2C+III+and+Daniel+Marcu%2E+2005%2E+A+Large%2Dscale+Exploration+of+Effective+Global+Features+for+a+Joint+Entity+Detection+and+Tracking+Model%2E+In+Proceedings+of+the+Conference+on+Empirical+Methods+in)
11. Pascal Denis and Jason Baldridge. 2008. Specialized Models and Ranking for Coreference Resolution. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. [find](https://scholar.google.com/scholar?q=Pascal+Denis+and+Jason+Baldridge%2E+2008%2E+Specialized+Models+and+Ranking+for+Coreference+Resolution%2E+In+Proceedings+of+the+Conference+on+Empirical+Methods+in+Natural+Language+Processing%2E) [our card](https://md.research.elamur.ai/free/papers/denis-2008-specialized-models-ranking-coreference-resolution/)
12. Mark Dredze, Paul McNamee, Delip Rao, Adam Gerber, and Tim Finin. 2010. Entity Disambiguation for Knowledge Base Population. In Proceedings of the International Conference on Computational Linguistics. [find](https://scholar.google.com/scholar?q=Mark+Dredze%2C+Paul+McNamee%2C+Delip+Rao%2C+Adam+Gerber%2C+and+Tim+Finin%2E+2010%2E+Entity+Disambiguation+for+Knowledge+Base+Population%2E+In+Proceedings+of+the+International+Conference+on+Computational+Linguistics)
13. John Duchi, Elad Hazan, and Yoram Singer. 2011. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. Journal of Machine Learning Research, 12:2121–2159, July. [find](https://scholar.google.com/scholar?q=John+Duchi%2C+Elad+Hazan%2C+and+Yoram+Singer%2E+2011%2E+Adaptive+Subgradient+Methods+for+Online+Learning+and+Stochastic+Optimization%2E+Journal+of+Machine+Learning+Research%2C+12%3A2121%E2%80%932159%2C+July%2E)
14. Greg Durrett and Dan Klein. 2013. Easy Victories and Uphill Battles in Coreference Resolution. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, October. [find](https://scholar.google.com/scholar?q=Greg+Durrett+and+Dan+Klein%2E+2013%2E+Easy+Victories+and+Uphill+Battles+in+Coreference+Resolution%2E+In+Proceedings+of+the+Conference+on+Empirical+Methods+in+Natural+Language+Processing%2C+October%2E) [our card](https://md.research.elamur.ai/free/papers/durrett-2013-easy-victories-uphill-battles-coreference/)
15. Greg Durrett, David Hall, and Dan Klein. 2013. Decentralized Entity-Level Modeling for Coreference Resolution. In Proceedings of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Greg+Durrett%2C+David+Hall%2C+and+Dan+Klein%2E+2013%2E+Decentralized+Entity%2DLevel+Modeling+for+Coreference+Resolution%2E+In+Proceedings+of+the+Association+for+Computational+Linguistics%2E) [our card](https://md.research.elamur.ai/free/papers/durrett-2013-decentralized-entity-level-modeling-coreference/)
16. Angela Fahrni and Michael Strube. 2014. A Latent Variable Model for Discourse-aware Concept and Entity Disambiguation. In Proceedings of the European Chapter of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Angela+Fahrni+and+Michael+Strube%2E+2014%2E+A+Latent+Variable+Model+for+Discourse%2Daware+Concept+and+Entity+Disambiguation%2E+In+Proceedings+of+the+European+Chapter+of+the+Association+for+Computational+Lingu)
17. Eraldo Rezende Fernandes, Cı́cero Nogueira dos Santos, and Ruy Luiz Milidiú. 2012. Latent Structure Perceptron with Feature Induction for Unrestricted Coreference Resolution. In Proceedings of the Joint Conference on Empirical Methods in Natural Language Proceedings and Conference on Computational… [find](https://scholar.google.com/scholar?q=Eraldo+Rezende+Fernandes%2C+C%C4%B1%CC%81cero+Nogueira+dos+Santos%2C+and+Ruy+Luiz+Milidiu%CC%81%2E+2012%2E+Latent+Structure+Perceptron+with+Feature+Induction+for+Unrestricted+Coreference+Resolution%2E+In+Proceedings+of+the+Jo) [our card](https://md.research.elamur.ai/free/papers/fernandes-2012-latent-structure-perceptron-feature-induction/)
18. Jenny Rose Finkel and Christopher D. Manning. 2009. Joint Parsing and Named Entity Recognition. In Proceedings of the North American Chapter for the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Jenny+Rose+Finkel+and+Christopher+D%2E+Manning%2E+2009%2E+Joint+Parsing+and+Named+Entity+Recognition%2E+In+Proceedings+of+the+North+American+Chapter+for+the+Association+for+Computational+Linguistics%2E)
19. Jenny Rose Finkel, Trond Grenager, and Christopher Manning. 2005. Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling. In Proceedings of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Jenny+Rose+Finkel%2C+Trond+Grenager%2C+and+Christopher+Manning%2E+2005%2E+Incorporating+Non%2Dlocal+Information+into+Information+Extraction+Systems+by+Gibbs+Sampling%2E+In+Proceedings+of+the+Association+for+Compu)
20. Kevin Gimpel and Noah A. Smith. 2010. Softmax-Margin CRFs: Training Log-Linear Models with Cost Functions. In Proceedings of the North American Chapter for the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Kevin+Gimpel+and+Noah+A%2E+Smith%2E+2010%2E+Softmax%2DMargin+CRFs%3A+Training+Log%2DLinear+Models+with+Cost+Functions%2E+In+Proceedings+of+the+North+American+Chapter+for+the+Association+for+Computational+Linguistic)
21. Yuhang Guo, Bing Qin, Yuqin Li, Ting Liu, and Sheng Li Li. 2013. Improving Candidate Generation for Entity Linking. In Natural Language Processing and Information Systems. [find](https://scholar.google.com/scholar?q=Yuhang+Guo%2C+Bing+Qin%2C+Yuqin+Li%2C+Ting+Liu%2C+and+Sheng+Li+Li%2E+2013%2E+Improving+Candidate+Generation+for+Entity+Linking%2E+In+Natural+Language+Processing+and+Information+Systems%2E)
22. Ben Hachey, Will Radford, Joel Nothman, Matthew Honnibal, and James R. Curran. 2013. Evaluating Entity Linking with Wikipedia. Artificial Intelligence, 194:130–150, January. [find](https://scholar.google.com/scholar?q=Ben+Hachey%2C+Will+Radford%2C+Joel+Nothman%2C+Matthew+Honnibal%2C+and+James+R%2E+Curran%2E+2013%2E+Evaluating+Entity+Linking+with+Wikipedia%2E+Artificial+Intelligence%2C+194%3A130%E2%80%93150%2C+January%2E)
23. Aria Haghighi and Dan Klein. 2009. Simple Coreference Resolution with Rich Syntactic and Semantic Features. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. [find](https://scholar.google.com/scholar?q=Aria+Haghighi+and+Dan+Klein%2E+2009%2E+Simple+Coreference+Resolution+with+Rich+Syntactic+and+Semantic+Features%2E+In+Proceedings+of+the+Conference+on+Empirical+Methods+in+Natural+Language+Processing%2E) [our card](https://md.research.elamur.ai/free/papers/haghighi-2009-simple-coreference-resolution-rich-syntactic/)
24. Aria Haghighi and Dan Klein. 2010. Coreference Resolution in a Modular, Entity-Centered Model. In Proceedings of the North American Chapter of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Aria+Haghighi+and+Dan+Klein%2E+2010%2E+Coreference+Resolution+in+a+Modular%2C+Entity%2DCentered+Model%2E+In+Proceedings+of+the+North+American+Chapter+of+the+Association+for+Computational+Linguistics%2E) [our card](https://md.research.elamur.ai/free/papers/haghighi-2010-coreference-resolution-modular-entity-centered/)
25. Hannaneh Hajishirzi, Leila Zilles, Daniel S. Weld, and Luke Zettlemoyer. 2013. Joint Coreference Resolution and Named-Entity Linking with Multi-Pass Sieves. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. [find](https://scholar.google.com/scholar?q=Hannaneh+Hajishirzi%2C+Leila+Zilles%2C+Daniel+S%2E+Weld%2C+and+Luke+Zettlemoyer%2E+2013%2E+Joint+Coreference+Resolution+and+Named%2DEntity+Linking+with+Multi%2DPass+Sieves%2E+In+Proceedings+of+the+Conference+on+Empiric) [our card](https://md.research.elamur.ai/free/papers/hajishirzi-2013-joint-coreference-resolution-named-entity/)
26. Johannes Hoffart, Mohamed Amir Yosef, Ilaria Bordino, Hagen Fürstenau, Manfred Pinkal, Marc Spaniol, Bilyana Taneva, Stefan Thater, and Gerhard Weikum. 2011. Robust Disambiguation of Named Entities in Text. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. [find](https://scholar.google.com/scholar?q=Johannes+Hoffart%2C+Mohamed+Amir+Yosef%2C+Ilaria+Bordino%2C+Hagen+Fu%CC%88rstenau%2C+Manfred+Pinkal%2C+Marc+Spaniol%2C+Bilyana+Taneva%2C+Stefan+Thater%2C+and+Gerhard+Weikum%2E+2011%2E+Robust+Disambiguation+of+Named+Entities+i)
27. Eduard Hovy, Mitchell Marcus, Martha Palmer, Lance Ramshaw, and Ralph Weischedel. 2006. OntoNotes: The 90% Solution. In Proceedings of the North American Chapter of the Association for Computational Linguistics: Short Papers. [find](https://scholar.google.com/scholar?q=Eduard+Hovy%2C+Mitchell+Marcus%2C+Martha+Palmer%2C+Lance+Ramshaw%2C+and+Ralph+Weischedel%2E+2006%2E+OntoNotes%3A+The+90%25+Solution%2E+In+Proceedings+of+the+North+American+Chapter+of+the+Association+for+Computational+L)
28. Heng Ji and Ralph Grishman. 2011. Knowledge Base Population: Successful Approaches and Challenges. In Proceedings of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Heng+Ji+and+Ralph+Grishman%2E+2011%2E+Knowledge+Base+Population%3A+Successful+Approaches+and+Challenges%2E+In+Proceedings+of+the+Association+for+Computational+Linguistics%2E)
29. Jun’ichi Kazama and Kentaro Torisawa. 2007. Exploiting Wikipedia as External Knowledge for Named Entity Recognition. In Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. [find](https://scholar.google.com/scholar?q=Jun%E2%80%99ichi+Kazama+and+Kentaro+Torisawa%2E+2007%2E+Exploiting+Wikipedia+as+External+Knowledge+for+Named+Entity+Recognition%2E+In+Proceedings+of+the+Joint+Conference+on+Empirical+Methods+in+Natural+Language+Pro)
30. Terry Koo, Xavier Carreras, and Michael Collins. 2008. Simple Semi-supervised Dependency Parsing. In Proceedings of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Terry+Koo%2C+Xavier+Carreras%2C+and+Michael+Collins%2E+2008%2E+Simple+Semi%2Dsupervised+Dependency+Parsing%2E+In+Proceedings+of+the+Association+for+Computational+Linguistics%2E) [our card](https://md.research.elamur.ai/free/papers/koo-2008-simple-semi-supervised-dependency-parsing/)
31. John D. Lafferty, Andrew McCallum, and Fernando C. N. Pereira. 2001. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. In Proceedings of the International Conference on Machine Learning. [find](https://scholar.google.com/scholar?q=John+D%2E+Lafferty%2C+Andrew+McCallum%2C+and+Fernando+C%2E+N%2E+Pereira%2E+2001%2E+Conditional+Random+Fields%3A+Probabilistic+Models+for+Segmenting+and+Labeling+Sequence+Data%2E+In+Proceedings+of+the+International+Conf)
32. Heeyoung Lee, Yves Peirsman, Angel Chang, Nathanael Chambers, Mihai Surdeanu, and Dan Jurafsky. 2011. Stanford’s Multi-Pass Sieve Coreference Resolution System at the CoNLL-2011 Shared Task. In Proceedings of the Conference on Computational Natural Language Learning: Shared Task. [find](https://scholar.google.com/scholar?q=Heeyoung+Lee%2C+Yves+Peirsman%2C+Angel+Chang%2C+Nathanael+Chambers%2C+Mihai+Surdeanu%2C+and+Dan+Jurafsky%2E+2011%2E+Stanford%E2%80%99s+Multi%2DPass+Sieve+Coreference+Resolution+System+at+the+CoNLL%2D2011+Shared+Task%2E+In+Procee) [our card](https://md.research.elamur.ai/free/papers/lee-2011-stanford-s-multi-pass-sieve/)
33. Qi Li and Heng Ji. 2014. Incremental Joint Extraction of Entity Mentions and Relations. In Proceedings of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Qi+Li+and+Heng+Ji%2E+2014%2E+Incremental+Joint+Extraction+of+Entity+Mentions+and+Relations%2E+In+Proceedings+of+the+Association+for+Computational+Linguistics%2E)
34. Xiaoqiang Luo. 2005. On Coreference Resolution Performance Metrics. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. [find](https://scholar.google.com/scholar?q=Xiaoqiang+Luo%2E+2005%2E+On+Coreference+Resolution+Performance+Metrics%2E+In+Proceedings+of+the+Conference+on+Empirical+Methods+in+Natural+Language+Processing%2E) [our card](https://md.research.elamur.ai/free/papers/luo-2005-coreference-resolution-performance-metrics/)
35. David Milne and Ian H. Witten. 2008. Learning to Link with Wikipedia. In Proceedings of the Conference on Information and Knowledge Management. [find](https://scholar.google.com/scholar?q=David+Milne+and+Ian+H%2E+Witten%2E+2008%2E+Learning+to+Link+with+Wikipedia%2E+In+Proceedings+of+the+Conference+on+Information+and+Knowledge+Management%2E)
36. Vincent Ng. 2010. Supervised Noun Phrase Coreference Research: The First Fifteen Years. In Proceedings of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Vincent+Ng%2E+2010%2E+Supervised+Noun+Phrase+Coreference+Research%3A+The+First+Fifteen+Years%2E+In+Proceedings+of+the+Association+for+Computational+Linguistics%2E) [our card](https://md.research.elamur.ai/free/papers/ng-2010-supervised-noun-phrase-coreference-research/)
37. NIST. 2005. The ACE 2005 Evaluation Plan. In NIST. [find](https://scholar.google.com/scholar?q=NIST%2E+2005%2E+The+ACE+2005+Evaluation+Plan%2E+In+NIST%2E)
38. Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, and James R. Curran. 2013. Learning Multilingual Named Entity Recognition from Wikipedia. Artificial Intelligence, 194:151–175, January. [find](https://scholar.google.com/scholar?q=Joel+Nothman%2C+Nicky+Ringland%2C+Will+Radford%2C+Tara+Murphy%2C+and+James+R%2E+Curran%2E+2013%2E+Learning+Multilingual+Named+Entity+Recognition+from+Wikipedia%2E+Artificial+Intelligence%2C+194%3A151%E2%80%93175%2C+January%2E)
39. Alexandre Passos, Vineet Kumar, and Andrew McCallum. 2014. Lexicon Infused Phrase Embeddings for Named Entity Resolution. In Proceedings of the Conference on Computational Natural Language Learning. [find](https://scholar.google.com/scholar?q=Alexandre+Passos%2C+Vineet+Kumar%2C+and+Andrew+McCallum%2E+2014%2E+Lexicon+Infused+Phrase+Embeddings+for+Named+Entity+Resolution%2E+In+Proceedings+of+the+Conference+on+Computational+Natural+Language+Learning%2E) [our card](https://md.research.elamur.ai/free/papers/passos-2014-lexicon-infused-phrase-embeddings-named/)
40. Slav Petrov, Leon Barrett, Romain Thibaux, and Dan Klein. 2006. Learning Accurate, Compact, and Interpretable Tree Annotation. In Proceedings of the Conference on Computational Linguistics and the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Slav+Petrov%2C+Leon+Barrett%2C+Romain+Thibaux%2C+and+Dan+Klein%2E+2006%2E+Learning+Accurate%2C+Compact%2C+and+Interpretable+Tree+Annotation%2E+In+Proceedings+of+the+Conference+on+Computational+Linguistics+and+the+Ass) [our card](https://md.research.elamur.ai/free/papers/aclbulk-2006-petrov-learning-accurate-compact-interpretable-tree/)
41. Simone Paolo Ponzetto and Michael Strube. 2006. Exploiting Semantic Role Labeling, WordNet and Wikipedia for Coreference Resolution. In Proceedings of the North American Chapter of the Association of Computational Linguistics. [find](https://scholar.google.com/scholar?q=Simone+Paolo+Ponzetto+and+Michael+Strube%2E+2006%2E+Exploiting+Semantic+Role+Labeling%2C+WordNet+and+Wikipedia+for+Coreference+Resolution%2E+In+Proceedings+of+the+North+American+Chapter+of+the+Association+of+) [our card](https://md.research.elamur.ai/free/papers/ponzetto-2006-exploiting-semantic-role-labeling-wordnet/)
42. Sameer Pradhan, Lance Ramshaw, Mitchell Marcus, Martha Palmer, Ralph Weischedel, and Nianwen Xue. 2011. CoNLL-2011 Shared Task: Modeling Unrestricted Coreference in OntoNotes. In Proceedings of the Conference on Computational Natural Language Learning: Shared Task. [find](https://scholar.google.com/scholar?q=Sameer+Pradhan%2C+Lance+Ramshaw%2C+Mitchell+Marcus%2C+Martha+Palmer%2C+Ralph+Weischedel%2C+and+Nianwen+Xue%2E+2011%2E+CoNLL%2D2011+Shared+Task%3A+Modeling+Unrestricted+Coreference+in+OntoNotes%2E+In+Proceedings+of+the+Co) [our card](https://md.research.elamur.ai/free/papers/pradhan-2011-conll-2011-shared-task-modeling/)
43. Sameer Pradhan, Alessandro Moschitti, Nianwen Xue, Olga Uryupina, and Yuchen Zhang. 2012. CoNLL-2012 Shared Task: Modeling Multilingual Unrestricted Coreference in OntoNotes. In Joint Conference on EMNLP and CoNLL - Shared Task. [find](https://scholar.google.com/scholar?q=Sameer+Pradhan%2C+Alessandro+Moschitti%2C+Nianwen+Xue%2C+Olga+Uryupina%2C+and+Yuchen+Zhang%2E+2012%2E+CoNLL%2D2012+Shared+Task%3A+Modeling+Multilingual+Unrestricted+Coreference+in+OntoNotes%2E+In+Joint+Conference+on+EM) [our card](https://md.research.elamur.ai/free/papers/pradhan-2012-conll-2012-shared-task-modeling/)
44. Sameer Pradhan, Xiaoqiang Luo, Marta Recasens, Eduard Hovy, Vincent Ng, and Michael Strube. 2014. Scoring Coreference Partitions of Predicted Mentions: A Reference Implementation. In Proceedings of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Sameer+Pradhan%2C+Xiaoqiang+Luo%2C+Marta+Recasens%2C+Eduard+Hovy%2C+Vincent+Ng%2C+and+Michael+Strube%2E+2014%2E+Scoring+Coreference+Partitions+of+Predicted+Mentions%3A+A+Reference+Implementation%2E+In+Proceedings+of+th) [our card](https://md.research.elamur.ai/free/papers/pradhan-2014-scoring-coreference-partitions-predicted-mentions/)
45. Karthik Raghunathan, Heeyoung Lee, Sudarshan Rangarajan, Nathanael Chambers, Mihai Surdeanu, Dan Jurafsky, and Christopher Manning. 2010. A Multi-Pass Sieve for Coreference Resolution. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. [find](https://scholar.google.com/scholar?q=Karthik+Raghunathan%2C+Heeyoung+Lee%2C+Sudarshan+Rangarajan%2C+Nathanael+Chambers%2C+Mihai+Surdeanu%2C+Dan+Jurafsky%2C+and+Christopher+Manning%2E+2010%2E+A+Multi%2DPass+Sieve+for+Coreference+Resolution%2E+In+Proceedings+) [our card](https://md.research.elamur.ai/free/papers/raghunathan-2010-multi-pass-sieve-coreference-resolution/)
46. Altaf Rahman and Vincent Ng. 2011. Coreference Resolution with World Knowledge. In Proceedings of the Association for Computational Linguistics: Human Language Technologies. [find](https://scholar.google.com/scholar?q=Altaf+Rahman+and+Vincent+Ng%2E+2011%2E+Coreference+Resolution+with+World+Knowledge%2E+In+Proceedings+of+the+Association+for+Computational+Linguistics%3A+Human+Language+Technologies%2E) [our card](https://md.research.elamur.ai/free/papers/rahman-2011-coreference-resolution-world-knowledge/)
47. Lev Ratinov and Dan Roth. 2009. Design Challenges and Misconceptions in Named Entity Recognition. In Proceedings of the Conference on Computational Natural Language Learning. [find](https://scholar.google.com/scholar?q=Lev+Ratinov+and+Dan+Roth%2E+2009%2E+Design+Challenges+and+Misconceptions+in+Named+Entity+Recognition%2E+In+Proceedings+of+the+Conference+on+Computational+Natural+Language+Learning%2E) [our card](https://md.research.elamur.ai/free/papers/ratinov-2009-design-challenges-misconceptions-named-entity/)
48. Lev Ratinov and Dan Roth. 2012. Learning-based Multi-sieve Co-reference Resolution with Knowledge. In Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. [find](https://scholar.google.com/scholar?q=Lev+Ratinov+and+Dan+Roth%2E+2012%2E+Learning%2Dbased+Multi%2Dsieve+Co%2Dreference+Resolution+with+Knowledge%2E+In+Proceedings+of+the+Joint+Conference+on+Empirical+Methods+in+Natural+Language+Processing+and+Comput) [our card](https://md.research.elamur.ai/free/papers/ratinov-2012-learning-based-multi-sieve-co/)
49. Lev Ratinov, Dan Roth, Doug Downey, and Mike Anderson. 2011. Local and Global Algorithms for Disambiguation to Wikipedia. In Proceedings of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Lev+Ratinov%2C+Dan+Roth%2C+Doug+Downey%2C+and+Mike+Anderson%2E+2011%2E+Local+and+Global+Algorithms+for+Disambiguation+to+Wikipedia%2E+In+Proceedings+of+the+Association+for+Computational+Linguistics%2E)
50. Avirup Sil and Alexander Yates. 2013. Re-ranking for Joint Named-Entity Recognition and Linking. In Proceedings of the International Conference on Information and Knowledge Management. [find](https://scholar.google.com/scholar?q=Avirup+Sil+and+Alexander+Yates%2E+2013%2E+Re%2Dranking+for+Joint+Named%2DEntity+Recognition+and+Linking%2E+In+Proceedings+of+the+International+Conference+on+Information+and+Knowledge+Management%2E)
51. Sameer Singh, Sebastian Riedel, Brian Martin, Jiaping Zheng, and Andrew McCallum. 2013. Joint Inference of Entities, Relations, and Coreference. In Proceedings of the 2013 Workshop on Automated Knowledge Base Construction. [find](https://scholar.google.com/scholar?q=Sameer+Singh%2C+Sebastian+Riedel%2C+Brian+Martin%2C+Jiaping+Zheng%2C+and+Andrew+McCallum%2E+2013%2E+Joint+Inference+of+Entities%2C+Relations%2C+and+Coreference%2E+In+Proceedings+of+the+2013+Workshop+on+Automated+Knowle)
52. David A. Smith and Jason Eisner. 2008. Dependency Parsing by Belief Propagation. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. [find](https://scholar.google.com/scholar?q=David+A%2E+Smith+and+Jason+Eisner%2E+2008%2E+Dependency+Parsing+by+Belief+Propagation%2E+In+Proceedings+of+the+Conference+on+Empirical+Methods+in+Natural+Language+Processing%2E)
53. Wee Meng Soon, Hwee Tou Ng, and Daniel Chung Yong Lim. 2001. A Machine Learning Approach to Coreference Resolution of Noun Phrases. Computational Linguistics, 27(4):521–544, December. [find](https://scholar.google.com/scholar?q=Wee+Meng+Soon%2C+Hwee+Tou+Ng%2C+and+Daniel+Chung+Yong+Lim%2E+2001%2E+A+Machine+Learning+Approach+to+Coreference+Resolution+of+Noun+Phrases%2E+Computational+Linguistics%2C+27%284%29%3A521%E2%80%93544%2C+December%2E) [our card](https://md.research.elamur.ai/free/papers/soon-2001-machine-learning-approach-coreference-resolution/)
54. Veselin Stoyanov, Nathan Gilbert, Claire Cardie, and Ellen Riloff. 2009. Conundrums in Noun Phrase Coreference Resolution: Making Sense of the State-of-the-Art. In Proceedings of the Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Veselin+Stoyanov%2C+Nathan+Gilbert%2C+Claire+Cardie%2C+and+Ellen+Riloff%2E+2009%2E+Conundrums+in+Noun+Phrase+Coreference+Resolution%3A+Making+Sense+of+the+State%2Dof%2Dthe%2DArt%2E+In+Proceedings+of+the+Association+for+C) [our card](https://md.research.elamur.ai/free/papers/stoyanov-2009-conundrums-noun-phrase-coreference-resolution/)
55. Veselin Stoyanov, Claire Cardie, Nathan Gilbert, Ellen Riloff, David Buttler, and David Hysom. 2010. Coreference Resolution with Reconcile. In Proceedings of the Association for Computational Linguistics: Short Papers. [find](https://scholar.google.com/scholar?q=Veselin+Stoyanov%2C+Claire+Cardie%2C+Nathan+Gilbert%2C+Ellen+Riloff%2C+David+Buttler%2C+and+David+Hysom%2E+2010%2E+Coreference+Resolution+with+Reconcile%2E+In+Proceedings+of+the+Association+for+Computational+Linguist) [our card](https://md.research.elamur.ai/free/papers/stoyanov-2010-coreference-resolution-reconcile/)
56. Marc Vilain, John Burger, John Aberdeen, Dennis Connolly, and Lynette Hirschman. 1995. A Model-Theoretic Coreference Scoring Scheme. In Proceedings of the Conference on Message Understanding. [find](https://scholar.google.com/scholar?q=Marc+Vilain%2C+John+Burger%2C+John+Aberdeen%2C+Dennis+Connolly%2C+and+Lynette+Hirschman%2E+1995%2E+A+Model%2DTheoretic+Coreference+Scoring+Scheme%2E+In+Proceedings+of+the+Conference+on+Message+Understanding%2E) [our card](https://md.research.elamur.ai/free/papers/vilain-1995-model-theoretic-coreference-scoring-scheme/)
57. Kellie Webster and James R. Curran. 2014. Limited Memory Incremental Coreference Resolution. In Proceedings of the Conference on Computational Linguistics. [find](https://scholar.google.com/scholar?q=Kellie+Webster+and+James+R%2E+Curran%2E+2014%2E+Limited+Memory+Incremental+Coreference+Resolution%2E+In+Proceedings+of+the+Conference+on+Computational+Linguistics%2E) [our card](https://md.research.elamur.ai/free/papers/webster-2014-limited-memory-incremental-coreference-resolution/)
58. Tong Zhang and David Johnson. 2003. A Robust Risk Minimization Based Named Entity Recognition System. In Proceedings of the Conference on Natural Language Learning. [find](https://scholar.google.com/scholar?q=Tong+Zhang+and+David+Johnson%2E+2003%2E+A+Robust+Risk+Minimization+Based+Named+Entity+Recognition+System%2E+In+Proceedings+of+the+Conference+on+Natural+Language+Learning%2E)
59. Jiaping Zheng, Luke Vilnis, Sameer Singh, Jinho D. Choi, and Andrew McCallum. 2013. Dynamic Knowledge-Base Alignment for Coreference Resolution. In Proceedings of the Conference on Computational Natural Language Learning. [find](https://scholar.google.com/scholar?q=Jiaping+Zheng%2C+Luke+Vilnis%2C+Sameer+Singh%2C+Jinho+D%2E+Choi%2C+and+Andrew+McCallum%2E+2013%2E+Dynamic+Knowledge%2DBase+Alignment+for+Coreference+Resolution%2E+In+Proceedings+of+the+Conference+on+Computational+Natur) [our card](https://md.research.elamur.ai/free/papers/zheng-2013-dynamic-knowledge-base-alignment-coreference/)