2021
ACL
ACL 2021
Three Sentences Are All You Need: Local Path Enhanced Document Relation Extraction
Abstract
AbstractDocument-level Relation Extraction (RE) is a more challenging task than sentence RE as it often requires reasoning over multiple sentences. Yet, human annotators usually use a small number of sentences to identify the relationship between a given entity pair. In this paper, we present an embarrassingly simple but effective method to heuristically select evidence sentences for document-level RE, which can be easily combined with BiLSTM to achieve good performance on benchmark datasets, even better than fancy graph neural network based methods. We have released our code at https://github.com/AndrewZhe/Three-Sentences-Are-All-You-Need.
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Keyword Pioneer
— document understanding
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Cross-Pollinator
— Artificial Intelligence, Deep Learning, Healthcare & Medicine, Knowledge & Reasoning, Machine Learning, Natural Language Processing
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
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Hot Topic Early Bird
— document-level relation extraction
Authors
Topics
Machine Learning > Core Methods > Classification
Deep Learning > Architectures > Neural Networks
Natural Language Processing > Applications > Information Extraction
Machine Learning > Core Methods > Sequence Modeling
Deep Learning > Architectures > Recurrent Neural Networks
Natural Language Processing > Applications > Relation Extraction