FarFetched: Entity-centric Reasoning and Claim Validation for the Greek Language based on Textually Represented Environments
Dimitris Papadopoulos, Katerina Metropoulou, Nikolaos Papadakis, Nikolaos Matsatsinis
Abstract
Our 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.- Anthology ID:
- 2022.deeplo-1.19
- Volume:
- Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing
- Month:
- July
- Year:
- 2022
- Address:
- Hybrid
- Editors:
- Colin Cherry, Angela Fan, George Foster, Gholamreza (Reza) Haffari, Shahram Khadivi, Nanyun (Violet) Peng, Xiang Ren, Ehsan Shareghi, Swabha Swayamdipta
- Venue:
- DeepLo
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 180–191
- Language:
- URL:
- https://aclanthology.org/2022.deeplo-1.19
- DOI:
- 10.18653/v1/2022.deeplo-1.19
- Cite (ACL):
- Dimitris Papadopoulos, Katerina Metropoulou, Nikolaos Papadakis, and Nikolaos Matsatsinis. 2022. FarFetched: Entity-centric Reasoning and Claim Validation for the Greek Language based on Textually Represented Environments. In Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing, pages 180–191, Hybrid. Association for Computational Linguistics.
- Cite (Informal):
- FarFetched: Entity-centric Reasoning and Claim Validation for the Greek Language based on Textually Represented Environments (Papadopoulos et al., DeepLo 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.deeplo-1.19.pdf
- Code
- lighteternal/farfetched_nlp
- Data
- FEVER