Yetisgen-Yildiz Meliha, Solti Imre, Xia Fei
Biomedical & Health Informatics, School of Medicine, University of Washington, Seattle, WA.
AMIA Annu Symp Proc. 2010;2010:1316.
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.
亚马逊的机械土耳其人（AMT）服务在自然语言处理（NLP）研究中越来越受欢迎。在本海报中，我们报告了使用AMT对从临床试验描述中提取的生物医学文本进行三种实体类型注释的研究结果：医疗状况、药物和实验室检查。我们还描述了对AMT工作人员注释的观察结果。
