{
    "Name": "PROBEL",
    "Volume": 47734.0,
    "Unit": "sentences",
    "License": "CC BY-NC-SA 4.0",
    "Link": "https://huggingface.co/collections/QCRI/media-integrity-intelligence",
    "HF_Link": "https://huggingface.co/collections/QCRI/media-integrity-intelligence",
    "Year": 2025,
    "Source": [
        "news articles",
        "social media"
    ],
    "Form": "text",
    "Domain": [
        "news",
        "politics",
        "society",
        "crisis"
    ],
    "Annotation_Style": [
        "human annotation"
    ],
    "Description": "Arabic-English propaganda detection resource",
    "Provider": [
        "Qatar Computing Research Institute",
        "University of Padova"
    ],
    "Derived_From": [
        "PropXplain"
    ],
    "Partial": false,
    "Paper_Title": "ProBel: Propaganda Detection with Techniques, Spans, and Explanations",
    "Paper_Link": "https://arxiv.org/pdf/2608.22388v1.pdf",
    "Tokenized": false,
    "Host": "HuggingFace",
    "Access": "Free",
    "Cost": "0",
    "Has_Splits": true,
    "Tasks": [
        "propaganda detection",
        "text classification"
    ],
    "Venue_Title": "arXiv",
    "Venue_Type": "preprint",
    "Venue_Name": "arXiv",
    "Authors": [
        "Mohamed Bayan Kmainasi",
        "Ali Ezzat Shahroor",
        "Elisa Sartori",
        "Giovanni Da San Martino",
        "Firoj Alam"
    ],
    "Affiliations": [
        "Qatar Computing Research Institute",
        "University of Padova"
    ],
    "Abstract": "Propaganda detection includes several related prediction levels, ranging from sentence-level decisions to technique classification and span identification. We present ProBel an Arabic and English resource that aligns binary labels, multi-label annotations over 23 propaganda techniques grouped into six coarse categories, technique-labeled spans, and reference explanations for the same news sentences. It includes a substantially larger English collection and supports matched binary, coarse-grained, multi-label, and span-level tasks in both languages.",
    "Dialect_Subsets": [],
    "Dialect": "mixed",
    "Language": "multilingual",
    "Script": "Arab-Latin",
    "Added_By": "qwen/qwen3.6-35b-a3b"
}