Abstract
In this paper we propose a novel model “recursive directed graph” based on feature structure, and apply it to represent the semantic relations of postpositive attributive structures in biomedical texts. The usages of postpositive attributive are complex and variable, especially three categories: present participle phrase, past participle phrase, and preposition phrase as postpositive attributive, which always bring the difficulties of automatic parsing. We summarize these categories and annotate the semantic information. Compared with dependency structure, feature structure, being recursive directed graph, enhances semantic information extraction in biomedical field. The annotation results show that recursive directed graph is more suitable to extract complex semantic relations for biomedical text mining.
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Foundation item: Supported by the National Natural Science Foundation of China (61202193, 61202304), the Major Projects of Chinese National Social Science Foundation (11&ZD189) and the Chinese Postdoctoral Science Foundation (2013M540593, 2014T70722)
Biography: CHEN Bo, female, Ph.D., Associate professor, research direction: natural language processing.
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Chen, B., Lü, C., Wei, X. et al. Semantic relation annotation for biomedical text mining based on recursive directed graph. Wuhan Univ. J. Nat. Sci. 20, 141–145 (2015). https://doi.org/10.1007/s11859-015-1072-2
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DOI: https://doi.org/10.1007/s11859-015-1072-2