Annotated Chemical Patent Corpus: A Gold Standard for Text Mining

Abstract

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.

Recognizing chemicals in patents: a comparative analysis

“…Chemical entities were manually annotated for 40 complete patent documents and normalized to CHEBI identifiers. The fourth corpus, noted here BioS, was prepared by the BioSemantics6 research group and covers 200 full patent documents [19]. For this corpus, patents were automatically pre-annotated and then manually curated by at least one annotator group consisting of two to ten annotators.…”

“…The annotation guidelines vary in several aspects. For instance, the IUPAC name “water” should not be annotated as a chemical in the CEMP corpora but it should be in the BioS corpus [19]. Additionally, simple chemical elements are annotated in the CEMP corpora but not in the BioS corpus.…”

“…Since 2012, two gold standard full-text patent corpora have been published: the chapati corpus [18] and the corpus from the BioSemantics research group [19]. The field was further boosted by a recent international competition, the CEMP task at BioCreative V. For this task, two large corpora for training and development were prepared and used by 21 teams to develop patent-specific solutions [20–22], achieving the F-measure values of up to 89% (87% precision and 91% recall) using an ensemble approach.…”

NERChem: adapting NERBio to chemical patents via full-token features and named entity feature with chemical sub-class composition

“…It divides the chemical names into several classes including ABBREVIATION, IDENTIFIER, FAMILY, FORMULA, MULTIPLE, SYSTEMATIC, TRIVIAL and NO_CLASS. CHEMDNER-patents (10) and Akhondi et al’s corpus (11) are CNR corpora of chemical patents. As previously mentioned, CHEMDNER-patents corpus was created using the same annotation platform and chemical classes as the CHEMDNER corpus with some additional rules.…”

Sources and Targets for Drug Repurposing: Landscaping Transitions in Therapeutic Space

“…11,12 Extracting such information from drawn structural formulas would be even more helpful and has been pursued for years, but is still highly experimental. 13,14 In effect, only an annotated chemical patent corpus 15 could provide a truly reliable data basis for automated identification of repurposing patents.…”