We describe the annotation of chemical named entities in scientific text. A set of annotation guidelines defines 5 types of named entities, and provides instructions for the resolution of special cases. A corpus of full-text chemistry papers was annotated, with an inter-annotator agreement score of 93%. An investigation of named entity recognition using LingPipe suggests that scores of 63% are possible without customisation, and scores of 74% are possible with the addition of custom tokenisation and the use of dictionaries.
CITATION STYLE
Corbett, P., Batchelor, C., & Teufel, S. (2007). Annotation of chemical named entities. In ACL 2007 - Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing (pp. 57–64). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1572392.1572403
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