Targum -- A Multilingual New Testament Translation Corpus

Links: 📄 LREC 2026 paper · 🤗 HuggingFace dataset · 🌐 Online viewer · 🧪 SIGHUM companion code

Targum is a multilingual New Testament translation corpus with unprecedented depth in five European languages: English, French, Italian, Polish, and Spanish. It contains 651 translations (334 unique) collected from 13 source libraries and spanning 1525–2025.

This repository contains the public release subset: 302 translations distributed under public domain or open licenses.

Named after the ancient Aramaic translations of the Hebrew Bible (תרגום, "translation"), the corpus prioritizes vertical depth over linguistic breadth, making it possible to computationally analyze a wide spectrum of historical periods and confessional traditions within each language.

This GitHub mirror ships the corpus texts and metadata tables. The companion HuggingFace dataset (mrapacz/targum-corpus) adds pre-computed embeddings (~120 GB) and pairwise similarity scores (~5 GB).

Corpus Scale

Language	Code	Total	Unique	Public subset
English	eng	390	194	191
French	fra	78	41	44
Spanish	spa	102	53	29
Polish	pol	48	29	25
Italian	ita	33	17	13
Total		651	334	302

"Total" is the number of translation instances collected across all 13 source libraries (the same translation may appear on multiple sites). "Unique" is the number of distinct translation editions after deduplication. "Public subset" is the number of instances distributed in this repository under public domain (237) or open licenses (65).

Structure

corpus/
  {site}/
    {iso}/
      {id}.jsonl     # one verse per line
works.tsv            # one row per translation work
editions.tsv         # one row per edition, with copyright + provenance
instances.tsv        # one row per per-site instance, FK to editions
book_coverage.tsv    # which books each instance covers
manifest.json        # summary statistics

# Same tables are also available as .json (lists preserved as arrays).

Each JSONL file contains one verse per line:

{"book": "MAT", "chapter": 1, "verse": "1", "text": "The book of the generation of Jesus Christ..."}
{"book": "MAT", "chapter": 1, "verse": "2", "text": "Abraham begat Isaac..."}

book uses USFM 3-letter New Testament codes: MAT MRK LUK JHN ACT ROM 1CO 2CO GAL EPH PHP COL 1TH 2TH 1TI 2TI TIT PHM HEB JAS 1PE 2PE 1JN 2JN 3JN JUD REV.

Embeddings

Pre-computed text embeddings are available for all translations, produced by several encoder models at chapter and/or verse granularity:

Model	Granularity	Files	Size
Qwen/Qwen3-Embedding-0.6B	verse	656	~7.7 GB
Qwen/Qwen3-Embedding-8B	chapter	656	~1007.1 MB
Qwen/Qwen3-Embedding-8B	verse	656	~74.5 GB
nvidia/llama-embed-nemotron-8b	chapter	656	~1007.5 MB
sentence-transformers/LaBSE	chapter	656	~1.1 GB
sentence-transformers/LaBSE	verse	656	~22.8 GB

Embeddings are stored as Hive-partitioned Parquet files under embeddings/ on HuggingFace:

embeddings/
  {model}/
    language={iso}/
      site={site}/
        translation={id}/
          granularity={chapter|verse}/
            data.parquet

Where {model} uses XxX as a separator (e.g. QwenXxXQwen3-Embedding-0.6B). Each data.parquet contains columns key (e.g. MAT 1 for chapter, MAT 1:1 for verse) and value (the embedding vector).

Loading chapter embeddings for one translation:

import pandas as pd

df = pd.read_parquet(
    "hf://datasets/mrapacz/targum-corpus/embeddings/"
    "QwenXxXQwen3-Embedding-0.6B/language=eng/site=ebible.org/"
    "translation=engwebp/granularity=chapter/data.parquet"
)

Similarity

The HuggingFace dataset also ships pairwise similarity scores between translations under similarity/:

• similarity/lexical/jaccard/chapter/{iso}.parquet -- chapter-level Jaccard token-overlap.
• similarity/lexical/levenshtein/chapter/{iso}.parquet -- chapter-level Levenshtein-based scores.
• similarity/semantic/cosine/{model}/chapter/{iso}.parquet -- chapter-level cosine similarity between embeddings (currently QwenXxXQwen3-Embedding-8B); a cross_language.parquet adds pairs that span language boundaries.

One parquet file per language at chapter granularity. Total payload is roughly 5 GB (lexical ~3 GB, semantic/cosine ~2 GB). See docs/targum-corpus/similarity.md for the exact definitions and reproduction steps.

Metadata

Each translation has three layers of metadata:

• works.tsv — one row per translation work (work_id, display name, abbreviation, language, tradition, reference URLs).
• editions.tsv — one row per distinct edition (FK work_id), with curated copyright_status / copyright_category / copyright_statement / copyright_statement_source_url / publisher / publication_year.
• instances.tsv — one row per per-site instance (FK edition_id, work_id), with site, iso, instance_id, counts (num_books, num_chapters, num_verses, num_words) and the per-site declared copyright.

This three-layer structure lets researchers define "uniqueness" however they need: by work (translation family), by edition (specific revision), or by per-site instance.

Quickstart

import json
from pathlib import Path

corpus = Path("corpus")
# Load one translation
verses = [json.loads(line) for line in (corpus / "ebible.org/eng/engwebp.jsonl").read_text().splitlines()]
print(f"{len(verses)} verses loaded")

# Load all English translations
translations = {}
for path in sorted(corpus.glob("*/eng/*.jsonl")):
    translations[path.stem] = [json.loads(line) for line in path.read_text().splitlines()]
print(f"{len(translations)} English translations")

Or via HuggingFace datasets (note: path prefix is corpora/ on HF):

from datasets import load_dataset

ds = load_dataset("mrapacz/targum-corpus", data_files="corpora/ebible.org/eng/engwebp.jsonl", split="train")

Source Data

Translations were collected from 13 libraries: bible.audio, bible.com, bible.is, biblegateway.com, biblehub.com, bibles.org, biblestudytools.com, bibliepolskie.pl, crossbible.com, ebible.org, jw.org, laparola.net, obohu.cz.

Only public domain and open-license translations are included in this release. The remaining 349 copyrighted translations are available to researchers upon reasonable request for noncommercial research purposes.

Citation

If you use this corpus, please cite our LREC 2026 paper:

Rapacz, M., & Smywiński-Pohl, A. (2026). Targum — a Multilingual New Testament Translation Corpus. In Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026) (pp. 7092–7105). European Language Resources Association (ELRA). https://doi.org/10.63317/2yiotxcyovir

@inproceedings{rapacz-etal-2026-targum,
  title     = {Targum -- a Multilingual New Testament Translation Corpus},
  author    = {Rapacz, Maciej and Smywi{\'n}ski-Pohl, Aleksander},
  booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026)},
  month     = {May},
  year      = {2026},
  pages     = {7092--7105},
  address   = {Palma, Mallorca, Spain},
  publisher = {European Language Resources Association (ELRA)},
  editor    = {Piperidis, Stelios and Bel, N{\'u}ria and van den Heuvel, Henk and Ide, Nancy and Krek, Simon and Toral, Antonio},
  doi       = {10.63317/2yiotxcyovir},
  url       = {https://lrec.elra.info/lrec2026-main-564}
}

Open-access PDF: http://www.lrec-conf.org/proceedings/lrec2026/pdf/2026.lrec2026-1.564.pdf.

License

Corpus metadata and derived annotations are released under CC-BY 4.0. Individual translations retain their original licenses as recorded in editions.tsv (copyright_statement column).