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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/988
Title: Relation extraction from text using supervised machine learning
Authors: Duong Thanh Hung 
Keywords: Natural language processing;Relation extraction;Supervised machine learning;SemEval 2010 Task 8 dataset
Issue Date: 2020
Abstract: 
In this thesis, we set out to investigate the task of relation extraction. In particular, we only concern about the relation classification step for binary relations. We conducted experiments with various settings, using BERT as the word representation. We also tested the idea of assigning "no relation" detection to a separate classifier. Overall, the single-classifier architecture yields the best performance. On the SemEval 2010 Task 8 dataset, it achieved the F1 score of 90.12%, and on the GDS dataset, it reached the average precision score of 85.05%. The duo classifier architecture does not fall far behind (89.98% F1 on the SemEval dataset)
URI(1): http://epub.vgu.edu.vn/handle/dlibvgu/988
Rights: Attribution-NonCommercial 4.0 International
Appears in Collections:Computer Science (CS)
Computer Science (CS)

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