2017
ACL
ACL 2017
Neural Architectures for Multilingual Semantic Parsing
Abstract
AbstractIn this paper, we address semantic parsing in a multilingual context. We train one multilingual model that is capable of parsing natural language sentences from multiple different languages into their corresponding formal semantic representations. We extend an existing sequence-to-tree model to a multi-task learning framework which shares the decoder for generating semantic representations. We report evaluation results on the multilingual GeoQuery corpus and introduce a new multilingual version of the ATIS corpus.
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Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
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Trend Setter
— Semantic Analysis
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Keyword Pioneer
— multilingual model
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Hot Topic Early Bird
— multi-task learning
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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, Speech & Audio
Authors
Topics
Natural Language Processing > Understanding > Semantic Analysis
Natural Language Processing > Resources & Methods > Multilingual NLP
Machine Learning > Learning Types > Multi-Task Learning
Machine Learning > Learning Paradigms > Multi-Task Learning
Natural Language Processing > Applications > Semantic Parsing