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FarFetched: Entity-centric Reasoning and Claim Validation for the Greek Language based on Textually Represented Environments

arXiv 2407.09888 ↗First posted 13 Jul 2024cs.CL cs.AIcited by 0

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Abstract (arXiv)

Our collective attention span is shortened by the flood of online information. With textitFarFetched, we address the need for automated claim validation based on the aggregated evidence derived from multiple online news sources. We introduce an entity-centric reasoning framework in which latent connections between events, actions, or statements are revealed via entity mentions and represented in a graph database. Using entity linking and semantic similarity, we offer a way for collecting and combining information from diverse sources in order to generate evidence relevant to the user's claim. Then, we leverage textual entailment recognition to quantitatively determine whether this assertion is credible, based on the created evidence. Our approach tries to fill the gap in automated claim validation for less-resourced languages and is showcased on the Greek language, complemented by the training of relevant semantic textual similarity (STS) and natural language inference (NLI) models that are evaluated on translated versions of common benchmarks.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 24 of its 45 references that are in the map. First posted on arXiv 13 Jul 2024.

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References · 24

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12 more
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  12. 2021PENELOPIE: Enabling Open Information Extraction for the Greek Language through Machine Translationcited by 3

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