Analyzing the Impact of Prevalence on the Evaluation of a Manual Annotation Campaign
Karën Fort | Claire François | Olivier Galibert | Maha Ghribi
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
This article details work aiming at evaluating the quality of the manual annotation of gene renaming couples in scientific abstracts, which generates sparse annotations. To evaluate these annotations, we compare the results obtained using the commonly advocated inter-annotator agreement coefficients such as S, κ and Ï, the less known R, the weighted coefficients κÏ and Î± as well as the F-measure and the SER. We analyze to which extent they are relevant for our data. We then study the bias introduced by prevalence by changing the way the contingency table is built. We finally propose an original way to synthesize the results by computing distances between categories, based on the produced annotations.