SlowGuess/NAACL_2022_OCR huggingface dataset:
winogender	winobias	WSC	DPR	all
Singular Personal	End-to-End	0.013	0.007	0.037	0.013	0.008
C&M	0.000	0.010	0.012	0.016	0.010
C&M++	0.016	0.011	0.075	0.016	0.013
BERT	0.199	0.146	0.060	0.141	0.145
SpanBERT	0.090	0.069	0.002	0.018	0.067
Plural	End-to-End	0.944	0.985	0.965	0.986	0.984
C&M	0.983	0.956	0.988	0.932	0.956
C&M++	0.998	0.990	0.909	0.983	0.988
BERT	0.949	0.836	0.944	0.966	0.846
SpanBERT	0.996	0.918	0.936	0.992	0.924
Singular Generic	End-to-End	0.200	0.443	0.047	0.108	0.416
C&M	0.033	0.010	0.023	0.014	0.011
C&M++	0.000	0.019	0.071	0.014	0.020
BERT	0.467	0.645	0.209	0.311	0.618
SpanBERT	0.350	0.515	0.163	0.149	0.490
Table 2: Model accuracies on WinoNB schemas containing different usages of "they".
A.2 Reformatted Results
For readability, we include the same results from Figure 2 in Table 2.
A.3 Licence Information for Used Datasets and Models
Winogender (Rudinger et al., 2018), Winobias (Zhao et al., 2018), C&M (Clark and Manning, 2016), and C&M++ (Wolf, 2017) are released under MIT licenses. End-to-End (Lee et al., 2018), BERT (Joshi et al., 2019), and Span-BERT (Joshi et al., 2020) are released under Apache License 2.0. WSC (Levesque et al., 2012) are released under a Creative Commons Attribution 4.0 International License. We did not find license information for DPR (Rahman and Ng, 2012). Our use of these data and models does not conflict with the licenses' stated access conditions.