metadata
license: cc-by-4.0
dataset_info:
features:
- name: english_reference
dtype: string
- name: hebrew_reference
dtype: string
- name: text
dtype: string
- name: transliteration
dtype: string
- name: translation
dtype: string
- name: dStrongs
dtype: string
- name: manuscript_source
dtype: string
splits:
- name: train
num_bytes: 30435977
num_examples: 305638
download_size: 13210659
dataset_size: 30435977
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
language:
- he
- en
tags:
- Bible
pretty_name: Original Language Bible Corpus -- Ancient Hebrew
Citation Information
If you use this data, please cite:
BibTeX:
@dataset{original_language_bibles,
author = {Hope McGovern},
title = {Original Language Bible Corpus: Ancient Hebrew Bible and Ancient Greek New Testament with Word-Level Translations},
year = {2024},
publisher = {Hugging Face Hub},
url = {https://huggingface.co/hmcgovern/original-language-bibles-greek},
note = {Includes word-level annotations and English translations for the Ancient Hebrew Bible (Old Testament) and Ancient Greek New Testament based on earliest manuscript evidence, compiled from STEP Bible (https://www.stepbible.org/).}
}
Aggregate to Line-Level
To aggregate this dataset to the line (verse) level, you can use a .map() function like this:
def aggregate_to_line(examples, priority='english'):
aggregated = {}
for ref, word, gloss in zip(examples[f"{priority}_reference"], examples["text"], examples["translation"]):
verse_key = ".".join(ref.split(".")[:-1]) # Extract the verse key (e.g., Gen.1.1)
if verse_key not in aggregated:
aggregated[verse_key] = {"texts": [], "translations": []}
aggregated[verse_key]["texts"].append(word)
aggregated[verse_key]["translations"].append(gloss)
# Convert the aggregated results into line-level entries
return {
"verse": list(aggregated.keys()),
"text": [" | ".join(aggregated[verse]["texts"]) for verse in aggregated],
"translation": [" | ".join(aggregated[verse]["translations"]) for verse in aggregated],
}
ds = ds.map(aggregate_to_line, batched=True, remove_columns=ds['train'].column_names, fn_kwargs={"priority": "hebrew"})
Where priority denotes whether to use English or Hebrew verse delineations. english priority -> 23_547 verses, hebrew priority -> 23_499 verses