| Literature DB >> 21785667 |
Meliha Yetisgen-Yildiz1, Imre Solti, Fei Xia.
Abstract
Amazon's Mechanical Turk (AMT) service is becoming increasingly popular in Natural Language Processing (NLP) research. In this poster, we report our findings in using AMT to annotate biomedical text extracted from clinical trial descriptions with three entity types: medical condition, medication, and laboratory test. We also describe our observations on AMT workers' annotations.Entities:
Year: 2010 PMID： 21785667 PMCID： PMC3140100
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN： 1559-4076