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Found 2 papers, 1 papers with code
A Unified Generative Framework based on Prompt Learning for Various Information Extraction Tasks
In this paper, we propose a novel composable prompt-based generative framework, which could be applied to a wide range of tasks in the field of Information Extraction.
StarGraph: Knowledge Representation Learning based on Incomplete Two-hop Subgraph
Conventional representation learning algorithms for knowledge graphs (KG) map each entity to a unique embedding vector, ignoring the rich information contained in the neighborhood.
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Link Property Prediction
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