Extracting molecular binding relationships from biomedical text
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
A practical part-of-speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Adjectival modification in text meaning representation
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Unsupervised, corpus-based method for extending a biomedical terminology
BioMed '02 Proceedings of the ACL-02 workshop on Natural language processing in the biomedical domain - Volume 3
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Objectives: To explore the phenomenon of adjectival modification in biomedical discourse across two genres: the biomedical literature and patient records. Methods: Adjectival modifiers are removed from phrases extracted from two corpora (three million noun phrases extracted from MEDLINE, on the one hand, and clinical notes from the Mayo Clinic, on the other). The original phrases, the adjectives extracted, and the resulting demodified phrases are compared across the two corpora after normalization. Quantitative comparisons (frequency of occurrence) are performed on the whole domain. Qualitative comparisons are performed on the two subdomains (disorders and procedures). Results: Although the average number of adjectives per phrase is equivalent in the two corpora (1.4), there are more adjective types in MAYO than in MEDLINE for disorders and procedures. For disorder phrases, the 38% of adjective types common to the two corpora account for 85% of the occurrences. The predominance of adjectives in one corpus is analyzed. Discussion: Potential applications of this approach are discussed, namely terminology acquisition, information retrieval, and genre characterization.