@inproceedings{li-etal-2018-analogical,
title = "Analogical Reasoning on {C}hinese Morphological and Semantic Relations",
author = "Li, Shen and
Zhao, Zhe and
Hu, Renfen and
Li, Wensi and
Liu, Tao and
Du, Xiaoyong",
editor = "Gurevych, Iryna and
Miyao, Yusuke",
booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P18-2023",
doi = "10.18653/v1/P18-2023",
pages = "138--143",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Analogical Reasoning on Chinese Morphological and Semantic Relations
%A Li, Shen
%A Zhao, Zhe
%A Hu, Renfen
%A Li, Wensi
%A Liu, Tao
%A Du, Xiaoyong
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F li-etal-2018-analogical
%X 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.
%R 10.18653/v1/P18-2023
%U https://aclanthology.org/P18-2023
%U https://doi.org/10.18653/v1/P18-2023
%P 138-143
Markdown (Informal)
[Analogical Reasoning on Chinese Morphological and Semantic Relations](https://aclanthology.org/P18-2023) (Li et al., ACL 2018)
ACL