2018
ACL
ACL 2018
CMMC-BDRC Solution to the NLP-TEA-2018 Chinese Grammatical Error Diagnosis Task
Abstract
AbstractChinese grammatical error diagnosis is an important natural language processing (NLP) task, which is also an important application using artificial intelligence technology in language education. This paper introduces a system developed by the Chinese Multilingual & Multimodal Corpus and Big Data Research Center for the NLP-TEA shared task, named Chinese Grammar Error Diagnosis (CGED). This system regards diagnosing errors task as a sequence tagging problem, while takes correction task as a text classification problem. Finally, in the 12 teams, this system gets the highest F1 score in the detection task and the second highest F1 score in mean in the identification task, position task and the correction task.
🌉
Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
📈
Trend Setter
— Syntax
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Keyword Pioneer
— grammatical error diagnosis
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Hot Topic Early Bird
— text classification
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio
Authors
Topics
Machine Learning > Core Methods > Classification
Natural Language Processing > Understanding > Syntax
Natural Language Processing > Applications > Text Classification
Machine Learning > Core Methods > Sequence Labeling
Natural Language Processing > Understanding > Text Classification
Natural Language Processing > Applications > Natural Language Understanding
Machine Learning > Learning Types > Sequence Labeling