Chinese Long and Short Form Choice Exploiting Neural Network Language Modeling Approaches

Lin Li, Kees van Deemter, Denis Paperno


Abstract
This paper presents our work in long and short form choice, a significant question of lexical choice, which plays an important role in many Natural Language Understanding tasks. Long and short form sharing at least one identical word meaning but with different number of syllables is a highly frequent linguistic phenomenon in Chinese like 老虎-虎(laohu-hu, tiger)
Anthology ID:
2020.ccl-1.81
Volume:
Proceedings of the 19th Chinese National Conference on Computational Linguistics
Month:
October
Year:
2020
Address:
Haikou, China
Editors:
Maosong Sun (孙茂松), Sujian Li (李素建), Yue Zhang (张岳), Yang Liu (刘洋)
Venue:
CCL
SIG:
Publisher:
Chinese Information Processing Society of China
Note:
Pages:
874–880
Language:
English
URL:
https://aclanthology.org/2020.ccl-1.81
DOI:
Bibkey:
Cite (ACL):
Lin Li, Kees van Deemter, and Denis Paperno. 2020. Chinese Long and Short Form Choice Exploiting Neural Network Language Modeling Approaches. In Proceedings of the 19th Chinese National Conference on Computational Linguistics, pages 874–880, Haikou, China. Chinese Information Processing Society of China.
Cite (Informal):
Chinese Long and Short Form Choice Exploiting Neural Network Language Modeling Approaches (Li et al., CCL 2020)
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PDF:
https://preview.aclanthology.org/nschneid-patch-2/2020.ccl-1.81.pdf