CLMay 10, 2017
A Survey of Deep Learning Methods for Relation Extraction
arXiv:1705.03645v1122 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental survey for researchers in information extraction, summarizing existing work without new results.
The paper surveys deep learning methods for relation extraction, comparing contributions and pitfalls of various models to guide future research.
Relation Extraction is an important sub-task of Information Extraction which has the potential of employing deep learning (DL) models with the creation of large datasets using distant supervision. In this review, we compare the contributions and pitfalls of the various DL models that have been used for the task, to help guide the path ahead.