Distant supervision relation extraction is a kind of relation extraction method.The existing methods,which mainly employ multi-instance learning and relation extraction,are conducted in the sample bag that contains the same entity pair.However,the bag-level method can only alleviate but cannot completely solve the problem of wrong la-beling.Therefore,herein,the distribution of clean data and noise data is analyzed,proposing a new self-adaptive loss function.On this basis,a method for sentence-level distant supervision relation extraction based on self-adaptive loss function is given.The experimental results obtained on the public dataset NYT-10 and the TACRED-based synthetic dataset show that the proposed method is better than that given in the compared studies.It can distinguish the wrongly labeled noise samples from the clean samples more effectively,improving the accuracy of sentence-level distant super-vision relation extraction.
关键词
自然语言处理/信息抽取/关系抽取/远程监督/噪声分离/噪声标注/负训练/自适应损失函数
Key words
natural language processing/information extraction/relation extraction/distant supervision/noise separa-tion/noise label/negative training/self-adaptive loss function
维普
万方数据