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            <namePart type="given">Michael</namePart>
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    <abstract>In this paper, we describe a system (CGSRC) for classifying four semantic relations: synonym, hypernym, antonym and meronym using convolutional neural networks (CNN). We have participated in CogALex-V semantic shared task of corpus-based identification of semantic relations. Proposed approach using CNN-based deep neural networks leveraging pre-compiled word2vec distributional neural embeddings achieved 43.15% weighted-F1 accuracy on subtask-1 (checking existence of a relation between two terms) and 25.24% weighted-F1 accuracy on subtask-2 (classifying relation types).</abstract>
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%0 Conference Proceedings
%T CogALex-V Shared Task: CGSRC - Classifying Semantic Relations using Convolutional Neural Networks
%A Guggilla, Chinnappa
%Y Zock, Michael
%Y Lenci, Alessandro
%Y Evert, Stefan
%S Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F guggilla-2016-cogalex
%X In this paper, we describe a system (CGSRC) for classifying four semantic relations: synonym, hypernym, antonym and meronym using convolutional neural networks (CNN). We have participated in CogALex-V semantic shared task of corpus-based identification of semantic relations. Proposed approach using CNN-based deep neural networks leveraging pre-compiled word2vec distributional neural embeddings achieved 43.15% weighted-F1 accuracy on subtask-1 (checking existence of a relation between two terms) and 25.24% weighted-F1 accuracy on subtask-2 (classifying relation types).
%U https://aclanthology.org/W16-5314
%P 104-109

Markdown (Informal)

[CogALex-V Shared Task: CGSRC - Classifying Semantic Relations using Convolutional Neural Networks](https://aclanthology.org/W16-5314) (Guggilla, CogALex 2016)

• CogALex-V Shared Task: CGSRC - Classifying Semantic Relations using Convolutional Neural Networks (Guggilla, CogALex 2016)

ACL

• Chinnappa Guggilla. 2016. CogALex-V Shared Task: CGSRC - Classifying Semantic Relations using Convolutional Neural Networks. In Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V), pages 104–109, Osaka, Japan. The COLING 2016 Organizing Committee.