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Developing a corpus of clinical notes manually annotated for part-of-speech
Serguei V. Pakhomov
, Anni Coden
, Christopher G. Chute
Chancellor's Office (Rochester)
Research output
:
Contribution to journal
›
Article
›
peer-review
37
Scopus citations
Overview
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Keyphrases
Clinical Notes
100%
Part-of
100%
Clinical Text
50%
Trigram
33%
Taggers
33%
Inter-rater Reliability
16%
Medical Data
16%
Set-aside
16%
Inter-rater Agreement
16%
Speech Information
16%
Discourse Type
16%
Manual Annotation
16%
Standard English
16%
English Text
16%
Speech Tagging
16%
Linguistic Annotation
16%
Penn Treebank
16%
Sublanguage
16%
Computer Science
Annotation
100%
Correctness
66%
Experimental Result
33%
Parts Of Speech Tagging
33%
Social Sciences
English
100%
Discourse
50%
Earth and Planetary Sciences
English
100%
State of the Art
50%
Mathematics
Statistical Testing
100%