The standard significance testing methods in NLP are therefore rank-or randomization-based nonparametric tests (Yeh, 2000;Riezler and Maxwell, 2005;Berg-Kirkpatrick et al., 2012).
most system comparisons across words, sentences or documents use bootstrap tests (Efron and Tibshirani, 1993) or approximate randomization (Noreen, 1989), while studies that compare performance across data sets use rank-based tests such as Wilcoxon's test.