Extracting Commonsense Properties from Embeddings with Limited Human Guidance

Yiben Yang, Larry Birnbaum, Ji-Ping Wang, Doug Downey

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Abstract
Intelligent systems require common sense, but automatically extracting this knowledge from text can be difficult. We propose and assess methods for extracting one type of commonsense knowledge, object-property comparisons, from pre-trained embeddings. In experiments, we show that our approach exceeds the accuracy of previous work but requires substantially less hand-annotated knowledge. Further, we show that an active learning approach that synthesizes common-sense queries can boost accuracy.
Anthology ID:
P18-2102
Volume:
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Month:
July
Year:
2018
Address:
Melbourne, Australia
Editors:
Iryna Gurevych, Yusuke Miyao
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
644–649
Language:
URL:
https://aclanthology.org/P18-2102
DOI:
10.18653/v1/P18-2102
Bibkey:
Cite (ACL):
Yiben Yang, Larry Birnbaum, Ji-Ping Wang, and Doug Downey. 2018. Extracting Commonsense Properties from Embeddings with Limited Human Guidance. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 644–649, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
Extracting Commonsense Properties from Embeddings with Limited Human Guidance (Yang et al., ACL 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/P18-2102.pdf
Software:
 P18-2102.Software.zip
Presentation:
 P18-2102.Presentation.pdf
Video:
 https://preview.aclanthology.org/teach-a-man-to-fish/P18-2102.mp4
Code
 yangyiben/PCE