2020
EMNLP
EMNLP 2020
Interpreting Open-Domain Modifiers: Decomposition of Wikipedia Categories into Disambiguated Property-Value Pairs
Abstract
AbstractThis paper proposes an open-domain method for automatically annotating modifier constituents (20th-century’) within Wikipedia categories (20th-century male writers) with properties (date of birth). The annotations offer a semantically-anchored understanding of the role of the constituents in defining the underlying meaning of the categories. In experiments over an evaluation set of Wikipedia categories, the proposed method annotates constituent modifiers as semantically-anchored properties, rather than as mere strings in a previous method. It does so at a better trade-off between precision and recall.
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Interdisciplinary Bridge
— Artificial Intelligence and Knowledge & Reasoning and Natural Language Processing
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Keyword Pioneer
— wikipedia categories
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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
Authors
Topics
Natural Language Processing > Understanding > Semantic Analysis
Natural Language Processing > Applications > Information Extraction
Knowledge & Reasoning > Representation > Knowledge Representation
Artificial Intelligence > Core AI > Knowledge Representation
Artificial Intelligence > Core AI > Knowledge Graph