Abstract
This paper presents a bidirectional transformer based approach for recognising semantic relationships between a pair of words as proposed by CogALex VI shared task in 2020. The system presented here works by employing BERT embeddings of the words and passing the same over tuned neural network to produce a learning model for the pair of words and their relationships. Afterwards the very same model is used for the relationship between unknown words from the test set. CogALex VI provided Subtask 1 as the identification of relationship of three specific categories amongst English pair of words and the presented system opts to work on that. The resulted relationships of the unknown words are analysed here which shows a balanced performance in overall characteristics with some scope for improvement.- Anthology ID:
- 2020.cogalex-1.8
- Volume:
- Proceedings of the Workshop on the Cognitive Aspects of the Lexicon
- Month:
- December
- Year:
- 2020
- Address:
- Online
- Venue:
- CogALex
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 65–71
- Language:
- URL:
- https://aclanthology.org/2020.cogalex-1.8
- DOI:
- Cite (ACL):
- Saurav Karmakar and John P. McCrae. 2020. CogALex-VI Shared Task: Bidirectional Transformer based Identification of Semantic Relations. In Proceedings of the Workshop on the Cognitive Aspects of the Lexicon, pages 65–71, Online. Association for Computational Linguistics.
- Cite (Informal):
- CogALex-VI Shared Task: Bidirectional Transformer based Identification of Semantic Relations (Karmakar & McCrae, CogALex 2020)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2020.cogalex-1.8.pdf