metadata

annotations_creators:
  - no-annotation
language:
  - de
  - fr
  - el
  - et
  - fi
  - hr
  - ji
  - pl
  - ru
  - sr
  - sv
  - uk
language_creators:
  - machine-generated
multilinguality:
  - multilingual
pretty_name: 'Europeana Newspapers '
size_categories:
  - 1M<n<10M
source_datasets: []
tags:
  - newspapers
  - lam
  - OCR
task_categories:
  - text-generation
task_ids:
  - language-modeling

Dataset Card for Dataset Name

This dataset contains historic newspapers from Europeana. In total the collection has ~32 Billion tokens. Documentation for this dataset is a WIP.

This dataset card aims to be a base template for new datasets. It has been generated using this raw template.

Dataset Details

Dataset Description

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Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
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Dataset Sources [optional]

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Uses

Direct Use

To download the full dataset using the Datasets library you can do the following

from datasets import load_dataset

dataset = load_dataset("biglam/europeana_newspapers")

You can also access a subset based on language or decade ranges using the following function.

from typing import List, Optional, Literal, Union
from huggingface_hub import hf_hub_url, list_repo_files

LanguageOption = Literal[
    "et",
    "pl",
    "sr",
    "ru",
    "sv",
    "no_language_found",
    "ji",
    "hr",
    "el",
    "uk",
    "fr",
    "fi",
    "de",
    "multi_language",
]


def get_files_for_lang_and_years(
    languages: Union[None, List[LanguageOption]] = None,
    min_year: Optional[int] = None,
    max_year: Optional[int] = None,
):
    files = list_repo_files("biglam/europeana_newspapers", repo_type="dataset")
    parquet_files = [f for f in files if f.endswith(".parquet")]
    parquet_files_filtered_for_lang = [
        f for f in parquet_files if any(lang in f for lang in ["uk", "fr"])
    ]
    filtered_files = [
        f
        for f in parquet_files
        if (min_year is None or min_year <= int(f.split("-")[1].split(".")[0]))
        and (max_year is None or int(f.split("-")[1].split(".")[0]) <= max_year)
    ]
    return [
        hf_hub_url("biglam/europeana_newspapers", f, repo_type="dataset")
        for f in filtered_files
    ]

This function takes a list of language codes, and a min, max value for decades you want to include. You can can use this function to get the URLs for files you want to download from the Hub:

ds = load_dataset("parquet", data_files=get_files_for_lang_and_years(['fr']), num_proc=4)

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Out-of-Scope Use

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Dataset Structure

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Dataset Creation

Curation Rationale

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Source Data

Data Collection and Processing

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Who are the source data producers?

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Annotations [optional]

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Bias, Risks, and Limitations

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Recommendations

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

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