ccel-paragraphs / README.md
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metadata
language:
  - en
dataset_info:
  features:
    - name: id
      dtype: string
    - name: text
      dtype: string
    - name: thml
      dtype: string
    - name: refs
      sequence: string
    - name: author
      dtype: string
    - name: title
      dtype: string
    - name: rights
      dtype: string
    - name: published
      dtype: string
    - name: all-MiniLM-L6-v2
      sequence: float64
  splits:
    - name: train
      num_bytes: 9776045339
      num_examples: 2215132
  download_size: 7000628494
  dataset_size: 9776045339

CCEL Paragraphs

Dataset Description

Dataset Summary

This dataset includes all paragraphs from the Christian Classics Ethereal Library. It also includes scripture references extracted from the ThML.

Supported Tasks and Leaderboards

It is expected that this dataset can be used as part of the training pipeline for large language models. In particular, it could be used to create a clustering benchmark by using scripture references as labels.

Languages

This dataset is primarily in English, but the dialects of English vary and span many centuries.

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

This includes a single "train" split with all paragraphs included.

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

[More Information Needed]

Contributions

Thanks to @jncraton for adding this dataset.