2019
ACL
ACL 2019
BSNLP2019 Shared Task Submission: Multisource Neural NER Transfer
Abstract
AbstractThis paper describes the Cognitive Computation (CogComp) Group’s submissions to the multilingual named entity recognition shared task at the Balto-Slavic Natural Language Processing (BSNLP) Workshop. The final model submitted is a multi-source neural NER system with multilingual BERT embeddings, trained on the concatenation of training data in various Slavic languages (as well as English). The performance of our system on the official testing data suggests that multi-source approaches consistently outperform single-source approaches for this task, even with the noise of mismatching tagsets.
🌉
Interdisciplinary Bridge
— Deep Learning and Natural Language Processing
🐝
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
Topics
Natural Language Processing > Understanding > Named Entity Recognition
Natural Language Processing > Resources & Methods > Multilingual NLP
Natural Language Processing > Applications > Named Entity Recognition
Deep Learning > Techniques > Transfer Learning
Deep Learning > Learning Types > Transfer Learning