We introduce Babbar26, a multilingual dataset of 1111 web pages from 1006 domains in five languages (English, French, German, Spanish, Italian), jointly annotated for genre, following a compact five-class taxonomy, and for main content and boilerplate, as main/noise regions anchored to the DOM. We describe the annotation guidelines and report double-annotation agreement on both tasks (97.1% on genre; content-level Cohen's k = 0.766 for main content). Compared with the classic KI-04 genre benchmark, a median page has 2.3x more DOM elements and 1.9x more readable text.

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