2 papers
cs.CL2019
NERO: A Neural Rule Grounding Framework for Label-Efficient Relation Extraction
Wenxuan Zhou, Hongtao Lin, Bill Yuchen Lin +4
Deep neural models for relation extraction tend to be less reliable when perfectly labeled data is limited, despite their success in label-sufficient scenarios. Instead of seeking…
cs.CL2019
Learning Dual Retrieval Module for Semi-supervised Relation Extraction
Hongtao Lin, Jun Yan, Meng Qu +1
Relation extraction is an important task in structuring content of text data, and becomes especially challenging when learning with weak supervision---where only a limited number o…