CogALex-V Shared Task: CGSRC - Classifying Semantic Relations using Convolutional Neural Networks
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).
PDF Abstract
Datasets
Add Datasets
introduced or used in this paper
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods
No methods listed for this paper. Add
relevant methods here
