RUG-1-Pegasussers at SemEval-2022 Task 3: Data Generation Methods to Improve Recognizing Appropriate Taxonomic Word Relations
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)(2022)
摘要
This paper describes our system created for the SemEval 2022 Task 3: Presupposed Taxonomies -Evaluating Neural-network Semantics.This task is focused on correctly recognizing taxonomic word relations in English, French and Italian.We develop various data generation techniques that expand the originally provided train set and show that all methods increase the performance of models trained on these expanded datasets.Our final system outperforms the baseline from the task organizers by achieving an average macro F1 score of 79.6 on all languages, compared to the baseline's 67.4.
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