Part-of-Speech Annotation of Biology Research Abstracts

Yuka Tateisi (1,2), Jun-ichi Tsujii (1,2)

(1) CREST/JST and (2)University of Tokyo

P14-W

A part-of-speech (POS) tagged corpus was built on research abstracts in biomedical domain with the Penn Treebank scheme. As consistent annotation was difficult without domain-specific knowledge we made use of the existing term annotation of the GENIA corpus. A list of frequent terms annotated in the GENIA corpus was compiled and the POS of each constituent of those terms were determined with assistance from domain specialists. The POS of the terms in the list are pre-assigned, then a tagger assigns POS to remaining words preserving the pre-assigned POS, whose results are corrected by human annotators. We also modified the PTB scheme slightly. An inter-annotator agreement tested on new 50 abstracts was 98.5%. A POS tagger trained with the annotated abstracts was tested against a gold-standard set made from the interannotator agreement. The untrained tagger had the accuracy of 83.0%. Trained with 2000 annotated abstracts the accuracy rose to 98.2%. The 2000 annotated abstracts are publicly available.

Part-of-speech corpus, Natural language processing in biology

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