CogNIAC: high precision coreference with limited knowledge and linguistic resources

Summary

CogNIAC is a rule-based pronoun resolution system designed for settings where deep linguistic knowledge and rich resources are not available. Its guiding idea is to favour precision over recall: a pronoun is resolved only when one of a small, ordered set of high-confidence rules applies, and is otherwise left unresolved rather than guessed. The rules rely on shallow cues such as uniqueness of a compatible antecedent in the current and preceding sentences, reflexives, possessives and grammatical role. Because each rule is simple and its firing is explicit, every resolution decision can be traced back to the rule that produced it. The paper argues that such a conservative resolver is useful as a component in larger systems, where a wrong link costs more than a missing one. It is an early, influential example of the "precise rules first" design later generalised by multi-pass sieve coreference systems.

How Mova uses it

• the development notes of coref, sieve speaker: the rules for first- and second-person pronouns within one voice ("I" of one speaker is one person; "we"/"you" of one voice are linked; "you" addressed to someone links to that addressee's earlier "I"; "I" inside a quotation refers to the subject of the speech verb outside it) are taken from Lee et al. 2013 (§3.3.1) together with Baldwin 1997.
• The broader CogNIAC principle — resolve only on a confident rule, otherwise abstain, and record which rule fired — matches the design of Mova's sieve coreference, where every link carries the id of the sieve that created it.

Effectiveness in Mova

The speaker sieve, whose rules are credited jointly to Lee et al. 2013 and this paper, is measured on the GUM test set (UD 2.18): 771 links at 90.7% precision, contributing +21.88 CoNLL F1 (without singletons, cumulative, on gold trees) and +21.99 on Mova's own parses. It is the first and most precise sieve. The share attributable to Baldwin 1997 alone is not measured separately.

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Topics: Coreference resolution

Cite

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

@inproceedings{baldwin1997cogniac,
  title = {{CogNIAC: high precision coreference with limited knowledge and linguistic resources}},
  author = {Baldwin, Breck},
  booktitle = {Operational Factors in Practical, Robust Anaphora Resolution for Unrestricted Texts},
  year = {1997},
  url = {https://aclanthology.org/W97-1306/}
}

References

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

1. Baldwin, B., "CogNIAC: A discourse processing engine", University of Pennsylvania, Department of Computer and Information Science, Ph.D. dissertation. find
2. Baldwin, B., Reynar, J., Collins, M., Eisner, J., Ratnaparkhi, A., Rosenzweig, J., Sarkar, A., Srinivas (1995), "University of Pennsylvania: Description of the University of Pennsylvania system used for MUC-6", Proceedings of Sixth Message Understanding Conference, November 1995. find
3. Collins, M., "A New Statistical Parser based on Bigram Lexical Dependencies", Proceedings of the 34th Annual Meeting of the Association for Computational Linguistics, June, 1996. find
4. Carter, D. (1986), "Common Sense Inference in a Focus-Guided Anaphor Resolver", Journal of Semantics, 4. find
5. Chinchor, N., Sundheim, B. (1994) "Coreference Task Definition vl.l", supporting documentation for MUC-6 coreference task. find
6. Dagan, I., Itai, A., (1990) A Statistical Filter for Resolving Pronoun References, Proceedings of 7th Israeli Symposium on Artificial Intelligence and Computer Vision. find
7. Grosz, B. J, Joshi, A. K., and Weinstein, S. (1986) "Towards a Computational Theory of Discourse Interpretation" Ms. find
8. Hobbs, J. (1976) "Pronoun Resolution", Research Report \#76-1, City College, City University of New York. find
9. Hobbs, J. (1977) "38 Examples of Elusive Antecedents from Published Texts", Research Report \#77-2, City College, City University of New York. find
10. C. Kennedy, B. Boguraev, "Anaphora for everyone: pronominal anaphora resolution without a parser." Proceedings of the 16th International Conference on Computational Linguistics COLING'96, Copenhagen, Denmark, 5-9 August 1996 find
11. Lappin, S., Leass, H. (1994) "An Algorithm for Pronominal Anaphora Resolution", Computational Linguistics. find our card
12. Mitkov R., "Pronoun resolution: the practical alternative", In S. Botley, T. McEnery (Eds) "Discourse Anaphora and Anaphor Resolution". University College London Press, 1997 find
13. Sidner, C. L. (1986) "Focusing in the Comprehension of Definite Anaphora", Readings in Natural Language Processing, eds Grosz, Jones, Webber. Morgan Kaufman, Los Altos CA. find
14. Winograd, T. 1972, "Understanding Natural Language", New York: Academic Press. find

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