2021
EMNLP
EMNLP 2021
The FairyNet Corpus - Character Networks for German Fairy Tales
Abstract
AbstractThis paper presents a data set of German fairy tales, manually annotated with character networks which were obtained with high inter rater agreement. The release of this corpus provides an opportunity of training and comparing different algorithms for the extraction of character networks, which so far was barely possible due to heterogeneous interests of previous researchers. We demonstrate the usefulness of our data set by providing baseline experiments for the automatic extraction of character networks, applying a rule-based pipeline as well as a neural approach, and find the neural approach outperforming the rule-approach in most evaluation settings.
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Interdisciplinary Bridge
— Computer Vision and Deep Learning and Interdisciplinary and Knowledge & Reasoning and Machine Learning and Natural Language Processing
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Keyword Pioneer
— german fairy tale
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Hot Topic Early Bird
— german language
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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
Deep Learning > Architectures > Graph Neural Networks
Computer Vision > Analysis > Scene Understanding
Natural Language Processing > Applications > Information Extraction
Natural Language Processing > Resources & Methods > Text Representation
Knowledge & Reasoning > Reasoning > Graph Embeddings
Interdisciplinary > Science > Digital Humanities
Machine Learning > Core Methods > Graph Neural Networks
Interdisciplinary > Digital Humanities