Abstract
We describe the performance of UtahPOET on SemEval 2015 Task 14. UtahPOET is a cognitively inspired system designed to extract semantic content from general clinical texts. We find that our system performs much better on the context slot-filling aspects of Tasks 2A and 2B than the disorder CUI mapping of Tasks 1 and 2B or the body location CUI mapping of Task 2B. Our problems with CUI mapping suggested several possible system improvements. An alteration in the correspondence between the system architecture and psycholinguistic findings is also indicated.
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CITATION STYLE
Doing-Harris, K., Igo, S., Shi, J., & Hurdle, J. (2015). UtahPOET: Disorder mention identification and context slot filling with cognitive inspiration. In SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings (pp. 399–405). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s15-2069
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