LASIGE: using Conditional Random Fields and ChEBI ontology
نویسندگان
چکیده
For participating in the SemEval 2013 challenge of recognition and classification of drug names, we adapted our chemical entity recognition approach consisting in Conditional Random Fields for recognizing chemical terms and lexical similarity for entity resolution to the ChEBI ontology. We obtained promising results, with a best F-measure of 0.81 for the partial matching task when using post-processing. Using only Conditional Random Fields the results are slightly lower, achieving still a good result in terms of Fmeasure. Using the ChEBI ontology allowed a significant improvement in precision (best precision of 0.93 in partial matching task), which indicates that taking advantage of an ontology can be extremely useful for enhancing chemical entity recognition.
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