Open Information Extraction Systems and Downstream Applications
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 4074-4076.
Abstract
Open Information Extraction (Open IE) extracts textual tuples comprising relation phrases and argument phrases from within a sentence, without requiring a pre-specified relation vocabulary. In this paper we first describe a decade of our progress on building Open IE extractors, which results in our latest extractor, OpenIE4, which is computationally efficient, outputs n-ary and nested relations, and also outputs relations mediated by nouns in addition to verbs. We also identify several strengths of the Open IE paradigm, which enable it to be a useful intermediate structure for end tasks. We survey its use in both human-facing applications and downstream NLP tasks, including event schema induction, sentence similarity, text comprehension, learning word vector embeddings, and more.
@inproceedings{ijcai2016p604,
title = {Open Information Extraction Systems and Downstream Applications},
author = {Mausam},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {4074--4076},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/604},
}
TY - CPAPER TI - Open Information Extraction Systems and Downstream Applications AU - Mausam T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 4074 EP - 4076 UR - https://ijcai.org/proceedings/2016/604 ER -Copied
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