2020
AACL
AACL 2020
Overview of NLPTEA-2020 Shared Task for Chinese Grammatical Error Diagnosis
Abstract
AbstractThis paper presents the NLPTEA 2020 shared task for Chinese Grammatical Error Diagnosis (CGED) which seeks to identify grammatical error types, their range of occurrence and recommended corrections within sentences written by learners of Chinese as a foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 30 teams registered for this shared task, 17 teams developed the system and submitted a total of 43 runs. System performances achieved a significant progress, reaching F1 of 91% in detection level, 40% in position level and 28% in correction level. All data sets with gold standards and scoring scripts are made publicly available to researchers.
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Conference Pioneer
— AACL 2020
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Interdisciplinary Bridge
— Interdisciplinary and Machine Learning and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio
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Hot Topic Early Bird
— error detection