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Extracting statistical mentions from textual claims to provide trusted content

Abstract : Claims on statistic (numerical) data, e.g., immigrant populations , are often fact-checked. We present a novel approach to extract from text documents, e.g., online media articles, mentions of statistic entities from a reference source. A claim states that an entity has certain value, at a certain time. This completes a fact-checking pipeline from text, to the reference data closest to the claim. We evaluated our method on the INSEE dataset and show that it is efficient and effective.
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https://hal.inria.fr/hal-02121389
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Submitted on : Monday, May 6, 2019 - 3:16:41 PM
Last modification on : Thursday, January 20, 2022 - 5:30:02 PM

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  • HAL Id : hal-02121389, version 1

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Tien Duc Cao, Ioana Manolescu, Xavier Tannier. Extracting statistical mentions from textual claims to provide trusted content. NLDB 2019 - 24th International Conference on Applications of Natural Language to Information Systems, Jun 2019, Salford, United Kingdom. ⟨hal-02121389⟩

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