FSN: Joint Entity and Relation Extraction Based on Filter Separator Network.

ABSTRACT: Joint entity and relation extraction methods have attracted an increasing amount of attention recently due to their capacity to extract relational triples from intricate texts. However, most of the existing methods ignore the association and difference between the Named Entity Recognition (NER) subtask features and the Relation Extraction (RE) subtask features, which leads to an imbalance in the interaction between these two subtasks. To solve the above problems, we propose a new joint entity and relation extraction method, FSN. It contains a Filter Separator Network (FSN) module that employs a two-direction LSTM to filter and separate the information contained in a sentence and merges similar features through a splicing operation, thus solving the problem of the interaction imbalance betw

SUBMITTER: Dai Q 

PROVIDER: S-EPMC10887558 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature