This tasks addresses the growing need to extract verified claims from the informal language found on social media. Unlike standard fact-checking pipelines that rely on well-formed input, our task aimed to rewrite user-generated content --often imprecise, opinionated, or fragmented-- into clear, concise, and factual statements, the way that human fact-checkers formulate the claims they are checking. The monolingual track covered thirteen languages, including English, German, French, Spanish, Portugese, Hindi, Marathi, Punjabi, Tamil, Arabic, Thai, Indonesian, and Polish.
Task results
| System | METEOR Sort ascending |
|---|---|
| DS@GT | 0.61 |
| dfkinit2b | 0.55 |
| AKCIT-FN | 0.52 |
| MMA | 0.51 |
| aryasuneesh | 0.39 |

