Noise-Tolerant Supervised Relation Extraction

Existing supervised relation extraction methods share generate flaws that they have improvable feature extractors and are uncapable of eliminating task-irrelevant words. To handle such issues, this paper proposed a relation extraction model that can avoid interference from task-irrelevant information. In this model, input texts are converted to digital sequences initially, and then these sequences...