【演講】2022.12.14The association between annotation consistency and model enhancement: a case study in BioNER task
開始日期
2022-12-14 13:00:00
結束日期
2022-12-14 15:00:00
活動說明
The association between annotation consistency and model enhancement: a case study in BioNER task
講者：黃明祥 博士後研究員 （Artificial Intelligence Pervasive Research Center , National Yang Ming Chiao Tung University）
日期 : 2022.12.14 星期三
時間 : 13:10-15:00
地點 : 台北醫學大學大安校區B2 （B201）
Abstract
Numerous text inputs are required to establish machine system for natural language processing （NLP）. The pre-labeled documents serve as datasets or corpora for system compilation. Therefore, the annotation quality of included corpus would mainly affect the machine efficacy.
In this topic, we briefly introduce the concept of annotation”, which is the foundation of text mining. The well-known Bio-NER corpus, JNLPBA, is used as an actual instance, and the reports from several systems on JNLPBA are provided to illustrate the phenomena of annotation inconsistency. Moreover, we revise JNLPBA corpus, and the corpus quality is measured by inter-annotator agreement （IAA） analysis. Lastly, the comparisons of system training on original/revised JNLPBA are applied to prove the association between annotation consistency and system performance.
