[BioNLP] New Paper on Recognition of Chemical Entities

Phil Gooch philgooch at gmail.com
Thu Apr 19 13:19:26 EDT 2012

Hi Ulf

Thanks for this. Unfortunately I don't have access to the full paper. Can I
ask: is the 68.1% F1 measure calculated using strict (exact boundary match)
or lenient (some overlap allowed) criteria?



On Sat, Apr 14, 2012 at 1:25 PM, Ulf Leser <leser at informatik.hu-berlin.de>wrote:

> See:
> http://bioinformatics.oxfordjournals.org/content/early/2012/04/11/bioinformatics.bts183.abstract
> ChemSpot: A Hybrid System for Chemical Named Entity Recognition
>     Tim Rocktäschel
>     Michael Weidlich
>     Ulf Leser
> Motivation: The accurate identification of chemicals in text is
> important for many applications, including computer-assisted
> reconstruction of metabolic networks or retrieval of information about
> substances in drug development. But due to the diversity of naming
> conventions and traditions for such molecules, this task is highly
> complex and should be supported by computational tools.
> Results: We present ChemSpot, a named entity recognition tool for
> identifying mentions of chemicals in natural language texts, including
> trivial names, drugs, abbreviations, molecular formulas and IUPAC
> entities. Since the different classes of relevant entities have rather
> different naming characteristics, ChemSpot uses a hybrid approach
> combining a Conditional Random Field with a dictionary. It achieves an
> F1 measure of 68.1% on the SCAI corpus, outperforming the only other
> freely available chemical named entity recognition tool, OSCAR4, by 10.8
> percentage points.
> Availability: ChemSpot is freely available at:
> http://www.informatik.hu-berlin.de/wbi/resources
> Best wishes,
> Ulf
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