--- title: "Pronominal and Sortal Anaphora Resolution for — Lin 2004" description: "The paper addresses automatic resolution of the two anaphora types most frequent in biomedical abstracts." authors: ["Yu-Hsiang Lin", "Tyne Liang"] year: 2004 venue: "Proceedings of the 16th Conference on Computational Linguistics and Speech Processing" source: "https://aclanthology.org/O04-1011/" 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/lin-2004-pronominal-sortal-anaphora-resolution-biomedical/" --- [Elamur Research](https://md.research.elamur.ai/) · [this page in HTML](https://research.elamur.ai/free/papers/lin-2004-pronominal-sortal-anaphora-resolution-biomedical/) [home](https://md.research.elamur.ai/) / [papers](https://md.research.elamur.ai/free/papers/) / [2004](https://md.research.elamur.ai/free/papers/2004/) / Pronominal and Sortal Anaphora Resolution for Biomedical Literature # Pronominal and Sortal Anaphora Resolution for Biomedical Literature **Authors:** [Yu-Hsiang Lin](https://md.research.elamur.ai/free/authors/yu-hsiang-lin/), [Tyne Liang](https://md.research.elamur.ai/free/authors/tyne-liang/) · **Year:** 2004 · **Venue:** Proceedings of the 16th Conference on Computational Linguistics and Speech Processing · **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/O04-1011/) · [PDF](https://aclanthology.org/O04-1011.pdf) · [OpenAlex](https://openalex.org/W2396229257) **Citations:** 18 citations (openalex-snapshot · 2026-10-14) · [5](#cited-by) in our library, of the 140673 papers whose bibliographies we read ## Summary The paper addresses automatic resolution of the two anaphora types most frequent in biomedical abstracts. The first is pronouns such as it, they and their. The second is sortal (definite) noun phrases, for example "these proteins", that point back to earlier biomedical entities. The authors' pipeline works in four steps: - It POS-tags and chunks the text. - It assigns grammatical roles with extended Siddharthan-style rules, including coordination rules for plural antecedents. - It removes pleonastic "it" and definite NPs that fall outside biomedical UMLS classes. - It enforces number agreement. Candidates from the two preceding sentences are then ranked by a salience score that mixes syntactic cues (recency, role preference and agreement, number) with semantic cues (LCS, UMLS semantic type agreement, biomedical antecedent). Semantic compatibility for pronouns relies on SA/AO patterns mined from GENIA 3.02p. For words missing from UMLS, the system uses headwords harvested from UMLS synonyms plus PubMed hit statistics. A genetic algorithm picks the best feature subset. On Medstract, the system reaches about 92% F-score for pronominal and 78% for sortal anaphora, outperforming Castaño et al. This matters for downstream relation extraction from MEDLINE. ## Key points - Resources used: UMLS 2003AC Metathesaurus, GENIA 3.02p (source of SA/AO patterns), WordNet 2.0 (hyponym matching) and PubMed query statistics. - Evaluation data: - Medstract: 32 MEDLINE abstracts with 83 anaphora pairs (26 pronominal, 57 sortal). - An additional in-house set of 103 MEDLINE abstracts with 177 pronominal pairs. - Results on Medstract: - The best-fit strategy with GA-selected features scored 92.31% F (pronominal) and 78.26% F (sortal). - Castaño et al. scored 75.23% and 74.4% respectively. - Nearest-fit was clearly weaker. - Syntactic features (F1–F4) help pronoun resolution but matter little for sortal anaphora. Semantic features (LCS, semantic type agreement, biomedical antecedent) are crucial for sortal anaphora. - Headword mining is the key aid for unknown words. Sortal F-score was 78% with both headwords and PubMed, 76% with headwords only, and about 58–59% without headwords. PubMed statistics added only a small gain. *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 5 papers of our library cite it (of the 140673 whose bibliographies we read); 2 of them have a page here, 3 not yet. - [Coreference Resolution for the Biomedical Domain: A Survey](https://md.research.elamur.ai/free/papers/lu-2021-coreference-resolution-biomedical-domain-survey/) - [Overview of BioNLP 2011 Protein Coreference Shared Task](https://md.research.elamur.ai/free/papers/nguyen-2011-overview-bionlp-2011-protein-coreference/) ## Cite The paper itself, not this page. BibTeX from the library's record of the work. ```bibtex @inproceedings{lin2004pronominal, title = {{Pronominal and Sortal Anaphora Resolution for Biomedical Literature}}, author = {Lin, Yu-Hsiang and Liang, Tyne}, booktitle = {Proceedings of the 16th Conference on Computational Linguistics and Speech Processing}, year = {2004}, url = {https://aclanthology.org/O04-1011/} } ``` - [← previous Parsing Ungrammatical Input: An Evaluation Procedure](https://md.research.elamur.ai/free/papers/lingbulk-2004-foster-parsing-ungrammatical-input-evaluation-procedure/) - [next → Rapid prototyping of a transfer-based Hebrew-to-English machine translation system](https://md.research.elamur.ai/free/papers/lavie-2004-rapid-prototyping-transfer-based-hebrew/) - [↑ back to papers of 2004](https://md.research.elamur.ai/free/papers/2004/) ## References 17 references, 7 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. [ 1] Breck Baldwin, “CogNIAC: high precision coreference with limited knowledge and linguistic resources,” In Proceedings of the ACL'97/EACL'97 workshop on Operational factors in practical, robust anaphora resolution, 1997, pp. 38-45. [find](https://scholar.google.com/scholar?q=%5B+1%5D+Breck+Baldwin%2C+%E2%80%9CCogNIAC%3A+high+precision+coreference+with+limited+knowledge+and+linguistic+resources%2C%E2%80%9D+In+Proceedings+of+the+ACL%2797%2FEACL%2797+workshop+on+Operational+factors+in+practical%2C+robust+ana) [our card](https://md.research.elamur.ai/free/papers/baldwin-1997-cogniac-high-precision-coreference-limited/) 2. 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