Analogical Reasoning on Chinese Morphological and Semantic Relations

Shen Li, Zhe Zhao, Renfen Hu, Wensi Li, Tao Liu, Xiaoyong Du


Abstract
Analogical reasoning is effective in capturing linguistic regularities. This paper proposes an analogical reasoning task on Chinese. After delving into Chinese lexical knowledge, we sketch 68 implicit morphological relations and 28 explicit semantic relations. A big and balanced dataset CA8 is then built for this task, including 17813 questions. Furthermore, we systematically explore the influences of vector representations, context features, and corpora on analogical reasoning. With the experiments, CA8 is proved to be a reliable benchmark for evaluating Chinese word embeddings.
Anthology ID:
P18-2023
Volume:
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Month:
July
Year:
2018
Address:
Melbourne, Australia
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
138–143
Language:
URL:
https://aclanthology.org/P18-2023
DOI:
10.18653/v1/P18-2023
Bibkey:
Cite (ACL):
Shen Li, Zhe Zhao, Renfen Hu, Wensi Li, Tao Liu, and Xiaoyong Du. 2018. Analogical Reasoning on Chinese Morphological and Semantic Relations. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 138–143, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
Analogical Reasoning on Chinese Morphological and Semantic Relations (Li et al., ACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/P18-2023.pdf
Poster:
 P18-2023.Poster.pdf
Code
 Embedding/Chinese-Word-Vectors +  additional community code