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fincorpus-de-10k

Languages:
English
German
Size:
10K<n<100K
Tags:
financial
bilingual
pdf
License:
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metadata
language:
  - en
  - de
tags:
  - financial
  - bilingual
  - pdf
pretty_name: FinCorpus-DE10k
annotations_creators:
  - no-annotation
language_creators:
  - found
size_categories:
  - 10K<n<100K
license: cc-by-nc-4.0
dataset_info:
  - config_name: BBK_monthly
    features:
      - name: filename
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: train
    download_size: 271752073
    dataset_size: 0
  - config_name: Law
    features:
      - name: filename
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: train
        num_bytes: 25707085
        num_examples: 134
    download_size: 271752073
    dataset_size: 25707085
  - config_name: all
    features:
      - name: filename
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: train
        num_bytes: 946487016
        num_examples: 10402
    download_size: 271752073
    dataset_size: 946487016
  - config_name: Annual_reports
    features:
      - name: filename
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: train
        num_bytes: 54268688
        num_examples: 87
    download_size: 271752073
    dataset_size: 54268688
  - config_name: Final_terms
    features:
      - name: filename
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: train
        num_bytes: 601219720
        num_examples: 9591
    download_size: 271752073
    dataset_size: 601219720
  - config_name: Base_prospectuses
    features:
      - name: filename
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: train
        num_bytes: 265291523
        num_examples: 590
    download_size: 271752073
    dataset_size: 265291523

Dataset Card for FinCorpus-DE10k

Dataset Details

Dataset Description

FinCorpus-DE10k is a corpus containing 12,235 PDF files of financial documents, mostly security prospectuses, along with plaintext files for approximately 10,500 of these documents. The documents are primarily in German (71%), with the rest being bilingual (German and English). This dataset aims to facilitate tasks like text analysis, language modeling, and document understanding in the financial domain.

This dataset is a subset of the above dataset, with the collections we felt comfortable releasing under permissive CC licenses. It omits the IFRS (containing 7 documents) and Informational_materials (127/129 txt/pdf files) collections. To get access to the full corpus, get in touch with us.

  • Curated by: Nata Kozaeva, Serhii Hamotskyi, Christian Hänig
  • Language(s) (NLP): German (DE), Bilingual (German and English)
  • License: CC BY-NC 4.0 except the monthly and annual reports, which are CC BY-NC-ND 4.0.

It's composed of multiple collections, with the text content available as dataset configs as:

  • Annual_reports
  • BBK_monthly
  • Base_prospectuses
  • Final_terms
  • Law
    • Repository: TODO
    • Paper: TODO

    Uses

    Direct Use

    By providing a rich collection of financial documents in PDF format, the dataset facilitates the development of algorithms that can navigate the complex layouts typically found in financial documents. FinCorpus-DE10k is also suited for developing and testing NLP models specialized in the financial domain, including but not limited to information extraction, named entity recognition, and specialized language models.

    Dataset Structure

    When used through load_dataset(), the dataset has two features: filename and text, one instance per .txt document.

    The complete dataset, pdf and txt, can be found in corpus.zip. In the archive, metadata.csv contains the path for the PDF and its extracted .txt (if available), as well as collection name, presence of extracted text, paths to PDF and .txt files, document language(s), and financial identifiers like ISIN and country for relevant documents.

    The pdf and txt subfolders contain the same mirrored directory structure, sorted by collection.

    Dataset Creation

    Source Data

    Data Collection and Processing

    Extensive preprocessing was applied to ensure the quality and uniformity of the dataset. It's described in our paper: TODO

    Who are the source data producers?

    The documents were produced by various financial institutions, regulatory bodies, companies, and the Deutsche Bundesbank.

    Personal and Sensitive Information

    The dataset contains financial documents that are publicly available.

    Licensing

    We diligently adhered to the licensing guidelines to the best of our understanding. However, the responsibility for the use of the documents and compliance with applicable laws rests with you.

    Get in touch with us if any of the documents need to be removed from the collection.

    Relevant links are: