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ccel-paragraphs

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ccel-paragraphs
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---
language:
- en
dataset_info:
  features:
  - name: id
    dtype: string
  - name: text
    dtype: string
  - name: thml
    dtype: string
  - name: refs
    sequence: string
  - name: all-MiniLM-L6-v2
    sequence: float64
  splits:
  - name: train
    num_bytes: 10610859675
    num_examples: 2428133
  download_size: 7687904847
  dataset_size: 10610859675
---
# CCEL Paragraphs

# Dataset Description

### Dataset Summary

This dataset includes all paragraphs from the [Christian Classics Ethereal Library](https://ccel.org/). It also includes scripture references extracted from the [ThML](https://en.wikipedia.org/wiki/Theological_Markup_Language).

### 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](https://github.com/jncraton) for adding this dataset.