CYUT at SemEval-2024 Task 7: A Numerals Augmentation and Feature Enhancement Approach to Numeral Reading Comprehension

AbstractThis study explores Task 2 in NumEval-2024, which is SemEval-2024(Semantic Evaluation)Task 7 , focusing on the Reading Comprehension of Numerals in Text (Chinese). The datasetutilized in this study is the Numeral-related Question Answering Dataset (NQuAD), and the model employed is BERT. The data undergoes preprocessing, incorporating Numerals Augmentation and Feature Enhancement to numerical entities before model training. Additionally, fine-tuning will also be applied. The result was an accuracy rate of 77.09%, representing a 7.14% improvement compared to the initial NQuAD processing model, referred to as the Numeracy-Enhanced Model (NEMo).