@inproceedings{jastrzebski-etal-2018-commonsense,
title = "Commonsense mining as knowledge base completion? A study on the impact of novelty",
author = "Jastrz{\k{e}}bski, Stanislaw and
Bahdanau, Dzmitry and
Hosseini, Seyedarian and
Noukhovitch, Michael and
Bengio, Yoshua and
Cheung, Jackie",
editor = "Bisk, Yonatan and
Levy, Omer and
Yatskar, Mark",
booktitle = "Proceedings of the Workshop on Generalization in the Age of Deep Learning",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-1002",
doi = "10.18653/v1/W18-1002",
pages = "8--16",
abstract = "Commonsense knowledge bases such as ConceptNet represent knowledge in the form of relational triples. Inspired by recent work by Li et al., we analyse if knowledge base completion models can be used to mine commonsense knowledge from raw text. We propose novelty of predicted triples with respect to the training set as an important factor in interpreting results. We critically analyse the difficulty of mining novel commonsense knowledge, and show that a simple baseline method that outperforms the previous state of the art on predicting more novel triples.",
}
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<abstract>Commonsense knowledge bases such as ConceptNet represent knowledge in the form of relational triples. Inspired by recent work by Li et al., we analyse if knowledge base completion models can be used to mine commonsense knowledge from raw text. We propose novelty of predicted triples with respect to the training set as an important factor in interpreting results. We critically analyse the difficulty of mining novel commonsense knowledge, and show that a simple baseline method that outperforms the previous state of the art on predicting more novel triples.</abstract>
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%0 Conference Proceedings
%T Commonsense mining as knowledge base completion? A study on the impact of novelty
%A Jastrzębski, Stanislaw
%A Bahdanau, Dzmitry
%A Hosseini, Seyedarian
%A Noukhovitch, Michael
%A Bengio, Yoshua
%A Cheung, Jackie
%Y Bisk, Yonatan
%Y Levy, Omer
%Y Yatskar, Mark
%S Proceedings of the Workshop on Generalization in the Age of Deep Learning
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F jastrzebski-etal-2018-commonsense
%X Commonsense knowledge bases such as ConceptNet represent knowledge in the form of relational triples. Inspired by recent work by Li et al., we analyse if knowledge base completion models can be used to mine commonsense knowledge from raw text. We propose novelty of predicted triples with respect to the training set as an important factor in interpreting results. We critically analyse the difficulty of mining novel commonsense knowledge, and show that a simple baseline method that outperforms the previous state of the art on predicting more novel triples.
%R 10.18653/v1/W18-1002
%U https://aclanthology.org/W18-1002
%U https://doi.org/10.18653/v1/W18-1002
%P 8-16
Markdown (Informal)
[Commonsense mining as knowledge base completion? A study on the impact of novelty](https://aclanthology.org/W18-1002) (Jastrzębski et al., Gen-Deep 2018)
ACL