@inproceedings{cui2018neural,
author = {Cui, Lei and Wei, Furu and Zhou, Ming},
title = {Neural Open Information Extraction},
booktitle = {ACL 2018},
year = {2018},
month = {July},
abstract = {Conventional Open Information Extraction (Open IE) systems are usually built on hand-crafted patterns from other NLP tools such as syntactic parsing, yet they face problems of error propagation. In this paper, we propose a neural Open IE approach with an encoder-decoder framework. Distinct from existing methods, the neural Open IE approach learns highly confident arguments and relation tuples bootstrapped from a state-of-the-art Open IE system. An empirical study on a large benchmark dataset shows that the neural Open IE system significantly outperforms several baselines, while maintaining comparable computational efficiency.},
publisher = {ACL 2018},
url = {http://approjects.co.za/?big=en-us/research/publication/neural-open-information-extraction/},
edition = {ACL 2018},
}