PharmaCoNER: Pharmacological Substances, Compounds and proteins Named Entity Recognition track (D19-57)
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Aitor Gonzalez-Agirre, Montserrat Marimon, Ander Intxaurrondo, Obdulia Rabal, Marta Villegas, Martin Krallinger
| Challenge: | Biomedical text mining is one of the most prolific application domains of natural language processing technologies. |
| Approach: | They propose to share a task on detecting drug and chemical entities in medical documents in Spanish with other languages to improve access to biomedical text mining. |
| Outcome: | The first task on detecting drug and chemical entities in Spanish medical documents yielded competitive results with F-measures above 0.91. |
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| Challenge: | Named entity recognition has been extensively studied on English news texts, but transfer to other domains and languages is still a challenging problem. |
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