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A Simple and Robust Approach to Detecting Subject Verb Agreement Errors

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Figure

Table 1: Performance of our systems (rule-based and LSTMs) and baselines. BERT-LM is the language modelbaseline.
Table 2: Performance (F0.5 scores) of the LSTM mo-dels when trained using an additional set of ‘clean’ sen-tences (cor) where non-SVA errors have been correc-ted.
Table 3: The Stanford PoS Tagger and DependencyParser’s performance on different treebanks
Figure 3: SVA error rates on the PTB data for complexsyntactic structures and ambiguous cases.

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