학술논문
Enhancing Document-level Relation Extraction with Integrated Local Evidence and Global Graph
Document Type
Conference
Author
Source
2024 4th Asia Conference on Information Engineering (ACIE) ACIE Information Engineering (ACIE), 2024 4th Asia Conference on. :138-142 Jan, 2024
Subject
Language
Abstract
Although deep learning excels in sentence-level relation extraction, document-level extraction poses challenges. To address this, we propose a neural network combining local and global entity representations, sourced directly from sentences. We construct mention-level graphs to capture intra and inter-entity connections. Utilizing advanced encoders like Bi-LSTM and BERT, our model effectively learns word representations from entity-linked text. Experiments on DocRED dataset yield impressive 57.33/59.84 Ign F1/F1 scores, a significant improvement over benchmarks.