Alleviating the Knowledge-Language Inconsistency: A Study for Deep
Commonsense Knowledge
- URL: http://arxiv.org/abs/2105.13607v2
- Date: Mon, 31 May 2021 13:09:19 GMT
- Title: Alleviating the Knowledge-Language Inconsistency: A Study for Deep
Commonsense Knowledge
- Authors: Yi Zhang, Lei Li, Yunfang Wu, Qi Su, Xu Sun
- Abstract summary: Deep commonsense knowledge occupies a significant part of commonsense knowledge.
We propose a novel method to mine the deep commonsense knowledge distributed in sentences.
- Score: 25.31716910260664
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Knowledge facts are typically represented by relational triples, while we
observe that some commonsense facts are represented by the triples whose forms
are inconsistent with the expression of language. This inconsistency puts
forward a challenge for pre-trained language models to deal with these
commonsense knowledge facts. In this paper, we term such knowledge as deep
commonsense knowledge and conduct extensive exploratory experiments on it. We
show that deep commonsense knowledge occupies a significant part of commonsense
knowledge while conventional methods fail to capture it effectively. We further
propose a novel method to mine the deep commonsense knowledge distributed in
sentences, alleviating the reliance of conventional methods on the triple
representation form of knowledge. Experiments demonstrate that the proposal
significantly improves the performance in mining deep commonsense knowledge.
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