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2020 SEMEVAL SemEval 2020

TüKaPo at SemEval-2020 Task 6: Def(n)tly Not BERT: Definition Extraction Using pre-BERT Methods in a post-BERT World

Abstract

AbstractWe describe our system (TüKaPo) submitted for Task 6: DeftEval, at SemEval 2020. We developed a hybrid approach that combined existing CNN and RNN methods and investigated the impact of purely-syntactic and semantic features on the task of definition extraction. Our final model achieved a F1-score of 0.6851 in subtask 1, i.e, sentence classification.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Madeeswaran Kannan , Haemanth Santhi Ponnusamy

Topics

Artificial Intelligence > Core AI > Multimodal Learning Machine Learning > Core Methods > Classification

Keywords

convolutional neural network recurrent neural network sentence classification hybrid approach definition extraction
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