FarFetched: entity-centric reasoning and claim validation for the Greek language based on textually represented environmentsFarFetched: entity-centric reasoning and claim validation for the Greek language based on textually represented environments Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2024-12-312022enOur collective attention span is shortened by the flood of online information. With FarFetched, 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.The research work of Dimitris Papadopoulos was supported by the Hellenic Foundation for Research and Innovation (HFRI) under the HFRI PhD Fellowship grant (Fellowship Number: 50, 2nd call).http://creativecommons.org/licenses/by/4.0/180-1913rd Workshop on Deep Learning Approaches for Low-Resource NLPProceedings of the DeepLo Workshop Papadopoulos Dimitrios Παπαδοπουλος Δημητριος Metropoulou Katerina Matsatsinis Nikolaos Ματσατσινης Νικολαος Papadakis Nikolaos Association for Computational Linguistics Natural languages Semantic similarity Textual similarities