Computational Linguistics
An algorithm for pronominal anaphora resolution
Computational Linguistics
Centering: a framework for modeling the local coherence of discourse
Computational Linguistics
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
Cognitive Status, Information Structure, and Pronominal Reference to Clausally Introduced Entities
Journal of Logic, Language and Information
On coreferring: coreference in MUC and related annotation schemes
Computational Linguistics
A corpus-based evaluation of centering and pronoun resolution
Computational Linguistics - Special issue on computational anaphora resolution
Description formation and discourse model synthesis
TINLAP '78 Proceedings of the 1978 workshop on Theoretical issues in natural language processing
Exploring semantic groups through visual approaches
Journal of Biomedical Informatics - Special issue: Unified medical language system
Design of the MUC-6 evaluation
MUC6 '95 Proceedings of the 6th conference on Message understanding
Improving machine learning approaches to coreference resolution
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Text and knowledge mining for coreference resolution
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Comparing Knowledge Sources for Nominal Anaphora Resolution
Computational Linguistics
Using the WordNet hierarchy for associative anaphora resolution
SEMANET '02 Proceedings of the 2002 workshop on Building and using semantic networks - Volume 11
Knowtator: a protégé plug-in for annotated corpus construction
NAACL-Demonstrations '06 Proceedings of the 2006 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume: demonstrations
A shared task involving multi-label classification of clinical free text
BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing
Resolving bridging references in unrestricted text
ANARESOLUTION '97 Proceedings of a Workshop on Operational Factors in Practical, Robust Anaphora Resolution for Unrestricted Texts
Specialized models and ranking for coreference resolution
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Anaphora and logical form: on formal meaning representations for natural language
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 1
Journal of Biomedical Informatics
Supervised models for coreference resolution
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Beyond NomBank: a study of implicit arguments for nominal predicates
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
An architecture for complex clinical question answering
Proceedings of the 1st ACM International Health Informatics Symposium
Journal of Biomedical Informatics
Stanford's multi-pass sieve coreference resolution system at the CoNLL-2011 shared task
CONLL Shared Task '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task
An improved corpus of disease mentions in PubMed citations
BioNLP '12 Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
Journal of Biomedical Informatics
Hi-index | 0.00 |
Motivation: Expressions that refer to a real-world entity already mentioned in a narrative are often considered anaphoric. For example, in the sentence ''The pain comes and goes,'' the expression ''the pain'' is probably referring to a previous mention of pain. Interpretation of meaning involves resolving the anaphoric reference: deciding which expression in the text is the correct antecedent of the referring expression, also called an anaphor. We annotated a set of 180 clinical reports (surgical pathology, radiology, discharge summaries, and emergency department) from two institutions to indicate all anaphor-antecedent pairs. Objective: The objective of this study is to describe the characteristics of the corpus in terms of the frequency of anaphoric relations, the syntactic and semantic nature of the members of the pairs, and the types of anaphoric relations that occur. Understanding how anaphoric reference is exhibited in clinical reports is critical to developing reference resolution algorithms and to identifying peculiarities of clinical text that may alter the features and methodologies that will be successful for automated anaphora resolution. Results: We found that anaphoric reference is prevalent in all types of clinical reports, that annotations of noun phrases, semantic type, and section headings may be especially important for automated resolution of anaphoric reference, and that separate modules for reference resolution may be required for different report types, different institutions, and different types of anaphors. Accurate resolution will probably require extensive domain knowledge-especially for pathology and radiology reports with more part/whole and set/subset relations. Conclusion: We hope researchers will leverage the annotations in this corpus to develop automated algorithms and will add to the annotations to generate a more extensive corpus.