CogALex-V Shared Task: LOPE

Kanan Luce, Jiaxing Yu, Shu-Kai Hsieh


Abstract
Automatic discovery of semantically-related words is one of the most important NLP tasks, and has great impact on the theoretical psycholinguistic modeling of the mental lexicon. In this shared task, we employ the word embeddings model to testify two thoughts explicitly or implicitly assumed by the NLP community: (1). Word embedding models can reflect syntagmatic similarities in usage between words to distances in projected vector space. (2). Word embedding models can reflect paradigmatic relationships between words.
Anthology ID:
W16-5315
Volume:
Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V)
Month:
December
Year:
2016
Address:
Osaka, Japan
Venues:
CogALex | WS
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
110–113
Language:
URL:
https://aclanthology.org/W16-5315
DOI:
Bibkey:
Cite (ACL):
Kanan Luce, Jiaxing Yu, and Shu-Kai Hsieh. 2016. CogALex-V Shared Task: LOPE. In Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V), pages 110–113, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
CogALex-V Shared Task: LOPE (Luce et al., 2016)
Copy Citation:
PDF:
https://aclanthology.org/W16-5315.pdf