WebFAQ: Large-Scale Multilingual FAQ Datasets for Dense Retrieval and Cross-Lingual QA

I’d like to share a new contribution to multilingual ML research: WebFAQ introduces a collection of 2.7 million natural question-answer pairs from real website FAQs across 8 languages (English, German, French, Spanish, Italian, Portuguese, Dutch, and Polish).

The key technical aspects:

• Unlike many multilingual datasets created through translation, WebFAQ preserves authentic question formulation in each language
• The extraction process preserved HTML formatting and structural elements, capturing real-world FAQ representation
• A multilingual parallel test set with 1,024 queries professionally translated into all 8 languages enables standardized cross-lingual evaluation
• Training embeddings on WebFAQ outperformed existing multilingual models like LaBSE, especially on cross-lingual retrieval
• The creation process used CommonCrawl data with regex and HTML parsing techniques, followed by quality filtering

I think this dataset addresses a major gap in multilingual information retrieval research. Most existing work relies on translated content that doesn’t capture how people naturally ask questions in different languages. The strong zero-shot cross-lingual performance suggests WebFAQ helps models develop more language-agnostic semantic understanding, which could improve global information access.

The uneven language distribution and European language focus are limitations, but this still represents progress toward more culturally-aware question answering systems. The parallel test set might prove particularly valuable as a standardized benchmark for future multilingual retrieval research.

TLDR: WebFAQ provides 2.7M natural Q&A pairs from web FAQs in 8 languages, proving effective for improving multilingual embedding models and cross-lingual retrieval capabilities.

Full summary is here. Paper here.