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metadata 
license: odc-by
dataset_info:
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configs:
  - config_name: deu_Latn
    data_files:
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        path: deu_Latn/train-*
  - config_name: spa_Latn
    data_files:
      - split: train
        path: spa_Latn/train-*
  - config_name: fra_Latn
    data_files:
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        path: fra_Latn/train-*
  - config_name: ita_Latn
    data_files:
      - split: train
        path: ita_Latn/train-*
language:
  - it
  - es
  - fr
  - de

fineweb-2-sample-60k-meta

Overview

This dataset is a metadata-enriched multilingual sample of the original FineWeb-2 dataset.

FineWeb-2 is a large-scale, high-quality web text corpus derived from Common Crawl, built through extensive filtering, deduplication, and language identification steps to support the training of modern large language models. It emphasizes text quality, diversity, and transparency, and includes rich crawl-level metadata inherited from Common Crawl.

This release contains a 60,000-entry sample drawn from FineWeb-2 and enriched with additional symbolic metadata layers aimed at improving interpretability, licensing awareness, and semantic analysis of web text.

Language Distribution

The dataset includes five languages, with an equal number of samples per language:

Language Subset Number of Entries Percentage
Italian ita_Latn 15,096 25%
French fra_Latn 15,054 25%
German deu_Latn 15,055 25%
Spanish spa_Latn 15,043 25%

Sampling Strategy

This dataset represents a small sample of the original FineWeb-2 corpus. The sampling preserves crawl-level provenance and the original FineWeb-2 filtering guarantees.

The goal is not to replace FineWeb-2, but to provide a research-oriented subset enriched with structured metadata that can support downstream analyses of licensing, content characteristics, and semantic properties.

Metadata Enrichment

Each document has been enriched with two complementary categories of metadata.

License-Related Metadata

License-related metadata aims to assess whether the original content may be considered permissively usable. For each document, we check:

  • whether the original URL is still reachable,
  • whether the website’s robots.txt allows crawler access,
  • whether the website explicitly mentions a license governing its content.

These signals are intended to support large-scale auditing and filtering, not to provide definitive legal judgments.

Semantics-Related Metadata

Semantics-related metadata is designed to provide a structured, symbolic interpretation of the text. Four main areas are covered:

  1. Formal features Including text length, readability, informativeness, and structural complexity.

  2. Entity focus Detection of people, organizations, temporal references, and geographical locations.

  3. Domain and topic classification Assignment of domains and subdomains describing the subject matter of the text.

  4. Content risk indicators Detection of potentially biased content, sensitive information, opinions, negativity, and personal data.

All semantics-related metadata has been extracted using an entirely symbolic processing stack, chosen for cost efficiency, scalability, and reproducibility.

In particular, semantic annotations were generated using the proprietary expert.ai knowledge graph.

Methodology Notes

  • No neural models were used for metadata extraction.
  • All annotations are deterministic and rule-based.
  • This design prioritizes computational efficiency, interpretability, and ease of large-scale deployment.

Work in Progress

This dataset represents an initial sample release. Work is ongoing to extend the same metadata enrichment pipeline to the entirety of FineWeb-2.

All future steps, methodological details, and validation results will be documented in a dedicated technical report.

Data Fields

Each entry includes the following fields:

Field Type Description
text string Main text content
id string Original unique identifier from Common Crawl
dump string Common Crawl dump this sample was extracted from
url string URL of the original web page
date string Crawl date (from Common Crawl)
file_path string S3 path of the Common Crawl WARC file
language string ISO 639-3 language code
language_score float64 Language prediction score from GlotLID
language_script string Script of the text (e.g. Latn)
minhash_cluster_size int64 Size of the MinHash cluster
top_langs string Language-script pairs with classifier scores
eai_lenChar string Length of the text in characters
eai_lenClass string Length class (clause, paragraph, article, book, etc.)
eai_readabilityLIX string LIX readability index
eai_readabilityEAI string Structural and semantic readability index
eai_readabilityCScore string Informativeness score
eai_quality string Indicators of processing difficulty
eai_geoClass string Detected geographic areas
eai_timeRef string Detected temporal references
eai_categories string Topics and domains
eai_subject string Types of referents detected
eai_metrics string Relevance of detected entity types
eai_idGeonames string GeoNames identifiers
eai_idWikiPeople string Wikipedia people identifiers
eai_idWikiOrg string Wikipedia organization identifiers
eai_idWikiGeo string Wikipedia location identifiers
eai_idWikiOther string Other Wikipedia entity identifiers
eai_idGoogleKGraph string Google Knowledge Graph identifiers
eai_idIATE string IATE (EU terminology) identifiers
eai_bias string Presence of biased content
eai_sensitiveContent string Presence of sensitive content
eai_opinions string Opinionated language indicators
eai_negativity string Negative sentiment
eai_privacy string Presence of personal data
eai_source string Source web domain
eai_urlReachable string Whether the URL is currently reachable
eai_robotsTxt string Robots.txt crawler permissions
eai_licenseInfo string License information detected on the website

Intended Use

This dataset is intended for:

  • research on licensing-aware data selection,
  • semantic analysis of large-scale web corpora,
  • multilingual text quality assessment,
  • development and evaluation of dataset auditing pipelines.

It is not intended to replace FineWeb-2, but to complement it with richer symbolic metadata.

Licensing

This dataset inherits the licensing considerations of the original FineWeb-2 corpus. The additional metadata is provided as-is and does not constitute legal advice regarding the usability of the underlying content.

Users are responsible for ensuring compliance with applicable licenses and terms of use.