A Comparison of Two Paraphrase Models for Taxonomy Augmentation

Vassilis Plachouras, Fabio Petroni, Timothy Nugent, Jochen L. Leidner

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Abstract
Taxonomies are often used to look up the concepts they contain in text documents (for instance, to classify a document). The more comprehensive the taxonomy, the higher recall the application has that uses the taxonomy. In this paper, we explore automatic taxonomy augmentation with paraphrases. We compare two state-of-the-art paraphrase models based on Moses, a statistical Machine Translation system, and a sequence-to-sequence neural network, trained on a paraphrase datasets with respect to their abilities to add novel nodes to an existing taxonomy from the risk domain. We conduct component-based and task-based evaluations. Our results show that paraphrasing is a viable method to enrich a taxonomy with more terms, and that Moses consistently outperforms the sequence-to-sequence neural model. To the best of our knowledge, this is the first approach to augment taxonomies with paraphrases.
Anthology ID:
N18-2051
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Marilyn Walker, Heng Ji, Amanda Stent
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
315–320
Language:
URL:
https://aclanthology.org/N18-2051
DOI:
10.18653/v1/N18-2051
Bibkey:
Cite (ACL):
Vassilis Plachouras, Fabio Petroni, Timothy Nugent, and Jochen L. Leidner. 2018. A Comparison of Two Paraphrase Models for Taxonomy Augmentation. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pages 315–320, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
A Comparison of Two Paraphrase Models for Taxonomy Augmentation (Plachouras et al., NAACL 2018)
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PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/N18-2051.pdf
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