YNU-oxz at SemEval-2020 Task 4: Commonsense Validation Using BERT with Bidirectional GRU

SEMEVAL 2020  ·  Xiaozhi Ou, Hongling Li ·

This paper describes the system and results of our team participated in SemEval-2020 Task4: Commonsense Validation and Explanation (ComVE), which aim to distinguish meaningful natural language statements from unreasonable natural language statements. This task contains three subtasks: Subtask A{--}Validation, Subtask B{--}Explanation (Multi-Choice), and Subtask C{--} Explanation (Generation). In these three subtasks, we only participated in Subtask A, which aims to distinguish whether a given two natural language statements with similar wording are meaningful. To solve this problem, we proposed a method using a combination of BERT with the Bidirectional Gated Recurrent Unit (Bi-GRU). Our model achieved an accuracy of 0.836 in Subtask A (ranked 27/45).

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