Modeling Script Knowledge for Machine Commonsense Reading Comprehension

• Main Authors: Hung-Kuo Liu, 劉宏國
• Other Authors: 陳信希
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/7ebdzq

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 107 === Introducing commonsense knowledge to the machine reading comprehension (MRC) task attracts attention in recent years. Most studies use ConceptNet to inference the abstract concepts and help their models answer the questions in reading comprehension. However, few studies employ Script knowledge to improve their MRC models. This thesis proposes a novel model for MRC by incorporating Script knowledge for modeling the various types of commonsense. Experimental results show that our model achieves the best performance on the MCScript dataset in the SemEval-2018 Task 11 and it increases the accuracy on the COIN dataset.