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Datasets:
Nacryos
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ancient-scripts-datasets

Tasks:
Text Classification
Token Classification
Modalities:
Tabular
Text
Formats:
parquet
Languages:
Multiple languages
Size:
10M - 100M
ArXiv:
Tags:
linguistics
historical-linguistics
cognate-detection
phylogenetics
ancient-languages
IPA
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ancient-scripts-datasets / README.md
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metadata 
language:
  - mul
license: cc-by-sa-4.0
task_categories:
  - text-classification
  - token-classification
tags:
  - linguistics
  - historical-linguistics
  - cognate-detection
  - phylogenetics
  - ancient-languages
  - IPA
  - phonetics
size_categories:
  - 10M<n<100M
configs:
  - config_name: cognate_pairs_inherited
    data_files:
      - split: train
        path: data/training/cognate_pairs/cognate_pairs_inherited.parquet
  - config_name: cognate_pairs_borrowing
    data_files:
      - split: train
        path: data/training/cognate_pairs/cognate_pairs_borrowing.parquet
  - config_name: cognate_pairs_similarity
    data_files:
      - split: train
        path: data/training/cognate_pairs/cognate_pairs_similarity.parquet
  - config_name: cognate_pairs_phono_filtered
    data_files:
      - split: train
        path: data/training/cognate_pairs/cognate_pairs_phono_filtered.parquet
  - config_name: linear_a_phonotactics_validation
    data_files:
      - split: train
        path: data/training/cognate_pairs/linear_a_phonotactics_validation.parquet
  - config_name: phylo_pairs
    data_files:
      - split: train
        path: data/training/metadata/phylo_pairs.parquet
  - config_name: languages
    data_files:
      - split: train
        path: data/training/metadata/languages.parquet

Ancient Scripts Decipherment Datasets

Collated datasets for the paper:

Deciphering Undersegmented Ancient Scripts Using Phonetic Prior Jiaming Luo, Frederik Hartmann, Enrico Santus, Regina Barzilay, Yuan Cao Transactions of the Association for Computational Linguistics, 2021 arXiv:2010.11054

This repository gathers the training datasets used in the paper — both those hosted in the authors' GitHub repos and the external cited sources.

Repository Structure 

data/
├── gothic/                          # Gothic language data
│   ├── got.pretrained.pth           # Pretrained phonological embeddings (PyTorch)
│   ├── segments.pkl                 # Phonetic segment data (Python pickle)
│   ├── gotica.txt                   # Gothic Bible plain text (Wulfila project)
│   └── gotica.xml.zip               # Gothic Bible TEI XML (Wulfila project)
│
├── ugaritic/                        # Ugaritic-Hebrew cognate data
│   ├── uga-heb.no_spe.cog          # Full cognate pairs (TSV, ~7,353 tokens)
│   └── uga-heb.small.no_spe.cog    # Small training subset (~10% of full)
│
├── iberian/                         # Iberian inscription data
│   └── iberian.csv                  # Cleaned Hesperia epigraphy (3,466 chunks)
│
├── religious_terms/                 # ** CURATED SUBSET: Religious vocabulary **
│   ├── README.md                    # Methodology and category definitions
│   ├── ugaritic_hebrew_religious.tsv  # ~170 Ug-Heb cognate pairs (deity, ritual, sacred)
│   ├── gothic_religious.tsv         # ~65 Gothic Bible religious terms
│   └── iberian_religious.tsv        # ~40 Iberian votive/religious elements
│
├── linear_b/                        # Linear B (Mycenaean Greek) dataset
│   ├── README.md                    # Sources, methodology, limitations
│   ├── linear_b_signs.tsv           # 211 signs (88 syllabograms + 123 ideograms)
│   ├── sign_to_ipa.json             # 74 syllabogram → IPA mappings
│   └── linear_b_words.tsv           # 2,484 words with IPA, glosses, sources
│
├── validation/                      # Phylogenetic validation dataset (9 branches)
│   ├── README.md                    # Format, sources, concept list
│   ├── concepts.tsv                 # 40 shared concept IDs
│   ├── germanic.tsv                 # got, ang, non, goh (~160 entries)
│   ├── celtic.tsv                   # sga, cym, bre (~120 entries)
│   ├── balto_slavic.tsv             # lit, chu, rus (~120 entries)
│   ├── indo_iranian.tsv             # san, ave, fas (~120 entries)
│   ├── italic.tsv                   # lat, osc, xum (~120 entries)
│   ├── hellenic.tsv                 # grc, gmy (~80 entries)
│   ├── semitic.tsv                  # heb, arb, amh (~120 entries)
│   ├── turkic.tsv                   # otk, tur, aze (~120 entries)
│   └── uralic.tsv                   # fin, hun, est (~120 entries)
│
└── cited_sources/                   # External datasets cited in the paper
    ├── genesis/
    │   ├── Hebrew.xml               # Hebrew Bible (Christodouloupoulos & Steedman 2015)
    │   └── Latin.xml                # Latin Bible (same corpus)
    ├── basque/
    │   ├── Basque-NT.xml            # Basque New Testament (same corpus)
    │   └── Trask_Etymological_Dictionary_Basque.pdf  # Trask's Basque etymological dictionary
    └── iberian_names/
        └── RodriguezRamos2014.pdf   # Iberian onomastic index (personal names)

Dataset Details

Gothic (data/gothic/)

File Source Description
got.pretrained.pth DecipherUnsegmented Pretrained phonological embeddings trained on Gothic IPA data
segments.pkl DecipherUnsegmented Serialized phonetic segment inventory
gotica.txt Wulfila Project Plain text of the Gothic Bible (4th century CE translation by Bishop Wulfila)
gotica.xml.zip Wulfila Project TEI P5 XML encoding with linguistic annotations

The Gothic Bible is the primary source of Gothic text. The paper uses unsegmented Gothic inscriptions from the 3rd-10th century AD period.

Ugaritic (data/ugaritic/)

File Source Description
uga-heb.no_spe.cog NeuroDecipher Full Ugaritic-Hebrew cognate pairs
uga-heb.small.no_spe.cog NeuroDecipher ~10% training subset

Format: Tab-separated values. Each row is a cognate pair. Column 1 = Ugaritic transliteration, Column 2 = Hebrew transliteration. | separates multiple cognates; _ marks missing entries. Originally from Snyder et al. (2010), covering 7,353 segmented tokens from the 14th-12th century BC.

Iberian (data/iberian/)

File Source Description
iberian.csv DecipherUnsegmented Cleaned epigraphic inscriptions

Format: CSV with columns REF. HESPERIA (inscription reference code) and cleaned (transcribed text). Contains 3,466 undersegmented character chunks from the 6th-1st century BC. Sourced from the Hesperia database and cleaned via the authors' Jupyter notebook.

Linear B / Mycenaean Greek (data/linear_b/)

File Source Description
linear_b_signs.tsv Unicode UCD 211 signs: 88 syllabograms + 123 ideograms with Bennett numbers and IPA
sign_to_ipa.json Ventris & Chadwick (1973) 74 syllabogram transliteration → IPA mappings
linear_b_words.tsv Multiple (see below) 2,478 words with IPA, glosses, and source attribution

Format: Tab-separated values. The word list contains columns: Word (transliteration), IPA, SCA (sound class), Source, Concept_ID, Cognate_Set_ID, Gloss, Word_Type, IPA_Source. Words come from three CC-BY-SA compatible sources: jhnwnstd/shannon Linear B Lexicon (MIT, 2,272 entries), Wiktionary Mycenaean Greek lemmas (CC-BY-SA, 170 entries with 46 expert IPA), and IE-CoR cognate pairs (42 entries). The sign inventory is from the Unicode Character Database.

Cited Sources (data/cited_sources/)

These are external datasets referenced in the paper for known-language vocabularies and comparison:

File Citation Usage in Paper
genesis/Hebrew.xml Christodouloupoulos & Steedman (2015) Hebrew vocabulary for Ugaritic comparison
genesis/Latin.xml Christodouloupoulos & Steedman (2015) Latin vocabulary for cross-linguistic comparison
basque/Basque-NT.xml Christodouloupoulos & Steedman (2015) Basque vocabulary for Iberian comparison
basque/Trask_Etymological_Dictionary_Basque.pdf Trask (2008) Basque etymological data
iberian_names/RodriguezRamos2014.pdf Rodriguez Ramos (2014) Iberian personal name lists with Latin correspondences

The Bible texts are from the Massively Parallel Bible Corpus (CC0 licensed).

Additional Data Sources (Not Included)

The following sources were cited in the paper but are not machine-readable or freely downloadable:

  • Wiktionary descendant trees for Proto-Germanic, Old Norse, and Old English vocabularies — extracted by the authors from Wiktionary's structured data
  • Original Hesperia epigraphy (hesperia_epigraphy.csv) — referenced in the DecipherUnsegmented README but not present in the repository

Cognate Detection Pipeline

The cognate_pipeline/ directory contains a full Python package for cross-linguistic cognate detection, built on the datasets in this repository. It provides:

  • Ingestion of CSV/TSV/COG, CLDF, Wiktionary JSONL, and generic JSON sources
  • Phonetic normalisation with transcription type tracking (IPA, transliteration, orthographic)
  • SCA sound class encoding (List 2012) for phonological comparison
  • Family-aware cognate candidate generation (tags cognate_inherited vs similarity_only)
  • Weighted Levenshtein scoring with SCA-class-aware substitution costs
  • Clustering via connected components or UPGMA
  • PostgreSQL/PostGIS database with 8 normalised tables and Alembic migrations
  • Export to CLDF Wordlist and JSON-LD formats
  • Full provenance tracking through every pipeline stage

Supports 36 languages across 9 phylogenetic branches (Germanic, Celtic, Balto-Slavic, Indo-Iranian, Italic, Hellenic, Semitic, Turkic, Uralic) plus isolates, with Glottocode resolution and IPA transcriptions.

See data/validation/README.md for the phylogenetic validation dataset.

See cognate_pipeline/README.md for installation and usage.

Original Repositories

Programmatic Access

Via HuggingFace datasets 

from datasets import load_dataset

# Load cognate pairs (Parquet, fast)
ds = load_dataset("Nacryos/ancient-scripts-datasets", "cognate_pairs_inherited")

# Available configs: cognate_pairs_inherited, cognate_pairs_borrowing,
# cognate_pairs_similarity, phylo_pairs, languages

Via Python SDK

For typed access with phylogenetic filtering, IPA parsing, and validation sets:

pip install git+https://github.com/Project-Phaistos/ancient-scripts-datasets-NEW.git

from ancient_scripts_data import AncientScriptsDataset

ds = AncientScriptsDataset()  # auto-downloads from HF
pairs = ds.cognate_pairs("inherited", phylo_filter="close_sister", limit=1000)
lex = ds.lexicon("lat")
rel = ds.phylo_relation("lat", "spa")  # near_ancestral

See the SDK documentation for full API reference.

Paper Citation 

@article{luo2021deciphering,
  title={Deciphering Undersegmented Ancient Scripts Using Phonetic Prior},
  author={Luo, Jiaming and Hartmann, Frederik and Santus, Enrico and Barzilay, Regina and Cao, Yuan},
  journal={Transactions of the Association for Computational Linguistics},
  volume={9},
  pages={69--81},
  year={2021},
  doi={10.1162/tacl_a_00354}
}