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82180337-semantic-rule-filtering-for-web-scale-relation-extraction.pdf
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📊 Size: 238 KB
📄 Pages: 16 pages
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Summary

Researchers propose a method to improve precision in web-scale relation extraction by utilizing a lexical semantic network, BabelNet, for semantic rule filtering. They apply Word Sense Disambiguation to automatically extracted rules and use the resulting relation-specific subgraphs as filters to estimate rule adequacy. This approach yields higher precision at any relative recall value in the high-recall range for seven tested semantic relations. The method introduces a novel unsupervised learning approach for building relation-specific lexical semantic graphs and demonstrates the effectiveness of BabelNet in improving relation extraction performance.

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Researchers propose a method to improve precision in web-scale relation extraction by utilizing a lexical semantic network, BabelNet, for semantic rule...

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  • File Format: PDF
  • File Size: 238 KB
  • Pages: 16
  • Language: EN
  • Total Downloads: 44
  • Last Updated: 3 weeks ago

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