FRINK Linked Data Fragments server

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• W2893600504 abstract "We aim to automatically generate natural language descriptions about an input structured knowledge base (KB). We build our generation framework based on a pointer network which can copy facts from the input KB, and add two attention mechanisms: (i) slot-aware attention to capture the association between a slot type and its corresponding slot value; and (ii) a new emph{table position self-attention} to capture the inter-dependencies among related slots. For evaluation, besides standard metrics including BLEU, METEOR, and ROUGE, we propose a KB reconstruction based metric by extracting a KB from the generation output and comparing it with the input KB. We also create a new data set which includes 106,216 pairs of structured KBs and their corresponding natural language descriptions for two distinct entity types. Experiments show that our approach significantly outperforms state-of-the-art methods. The reconstructed KB achieves 68.8% - 72.6% F-score." @default.
• W2893600504 created "2018-10-05" @default.
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• W2893600504 date "2018-01-01" @default.
• W2893600504 modified "2023-09-28" @default.
• W2893600504 title "Describing a Knowledge Base" @default.
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• W2893600504 doi "https://doi.org/10.18653/v1/w18-6502" @default.
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