2020
SEMEVAL
SemEval 2020
Gorynych Transformer at SemEval-2020 Task 6: Multi-task Learning for Definition Extraction
Abstract
AbstractThis paper describes our approach to “DeftEval: Extracting Definitions from Free Text in Textbooks” competition held as a part of Semeval 2020. The task was devoted to finding and labeling definitions in texts. DeftEval was split into three subtasks: sentence classification, sequence labeling and relation classification. Our solution ranked 5th in the first subtask and 23rd and 21st in the second and the third subtasks respectively. We applied simultaneous multi-task learning with Transformer-based models for subtasks 1 and 3 and a single BERT-based model for named entity recognition.
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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