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REMI: Mining Intuitive Referring Expressions on Knowledge Bases

Luis Galárraga 1 Julien Delaunay 2 Jean-Louis Dessalles 3
1 LACODAM - Large Scale Collaborative Data Mining
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : A referring expression (RE) is a description that identifies a set of instances unambiguously. Mining REs from data finds applications in natural language generation, algorithmic journalism, and data maintenance. Since there may exist multiple REs for a given set of entities, it is common to focus on the most concise and informative (i.e., intuitive) ones. We present REMI, a method to mine intuitive REs on large knowledge bases. Our experimental evaluation shows that REMI finds REs deemed intuitive by users. Moreover we show that REMI is several orders of magnitude faster than an approach based on inductive logic programming.
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https://hal.inria.fr/hal-03084627
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Submitted on : Wednesday, February 3, 2021 - 12:47:04 PM
Last modification on : Tuesday, October 19, 2021 - 11:04:41 AM
Long-term archiving on: : Tuesday, May 4, 2021 - 6:01:20 PM

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Luis Galárraga, Julien Delaunay, Jean-Louis Dessalles. REMI: Mining Intuitive Referring Expressions on Knowledge Bases. EDBT 2020 - 23rd International Conference on Extending Database Technology, Mar 2020, Virtual Event, Denmark. pp.387-390, ⟨10.5441/002/edbt.2020.39⟩. ⟨hal-03084627⟩

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