Annotated chemical patent corpus: a gold standard for text mining.
Annotated chemical patent corpus: a gold standard for text mining.
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DOI:
10.1371/journal.pone.0107477
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发表时间:
2014
期刊:
影响因子:
3.7
通讯作者:
Muresan S
中科院分区:
文献类型:
--
作者:
Akhondi SA;Klenner AG;Tyrchan C;Manchala AK;Boppana K;Lowe D;Zimmermann M;Jagarlapudi SA;Sayle R;Kors JA;Muresan S
Exploring the chemical and biological space covered by patent applications is crucial in early-stage medicinal chemistry activities. Patent analysis can provide understanding of compound prior art, novelty checking, validation of biological assays, and identification of new starting points for chemical exploration. Extracting chemical and biological entities from patents through manual extraction by expert curators can take substantial amount of time and resources. Text mining methods can help to ease this process. To validate the performance of such methods, a manually annotated patent corpus is essential. In this study we have produced a large gold standard chemical patent corpus. We developed annotation guidelines and selected 200 full patents from the World Intellectual Property Organization, United States Patent and Trademark Office, and European Patent Office. The patents were pre-annotated automatically and made available to four independent annotator groups each consisting of two to ten annotators. The annotators marked chemicals in different subclasses, diseases, targets, and modes of action. Spelling mistakes and spurious line break due to optical character recognition errors were also annotated. A subset of 47 patents was annotated by at least three annotator groups, from which harmonized annotations and inter-annotator agreement scores were derived. One group annotated the full set. The patent corpus includes 400,125 annotations for the full set and 36,537 annotations for the harmonized set. All patents and annotated entities are publicly available at www.biosemantics.org.
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影响因子:
5.6
作者:
Sayle, Roger;Xie, Paul Hongxing;Muresan, Sorel
通讯作者:
Muresan, Sorel
影响因子:
8.6
作者:
Akhondi SA;Kors JA;Muresan S
通讯作者:
Muresan S
影响因子:
8.6
作者:
Southan C;Boppana K;Jagarlapudi SA;Muresan S
通讯作者:
Muresan S
影响因子:
8.6
作者:
Jessop DM;Adams SE;Murray-Rust P
通讯作者:
Murray-Rust P
影响因子:
8.6
作者:
Heller S;McNaught A;Stein S;Tchekhovskoi D;Pletnev I
通讯作者:
Pletnev I