--- 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 **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](https://arxiv.org/abs/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](https://github.com/j-luo93/DecipherUnsegmented) | Pretrained phonological embeddings trained on Gothic IPA data | | `segments.pkl` | [DecipherUnsegmented](https://github.com/j-luo93/DecipherUnsegmented) | Serialized phonetic segment inventory | | `gotica.txt` | [Wulfila Project](https://www.wulfila.be/gothic/download/) | Plain text of the Gothic Bible (4th century CE translation by Bishop Wulfila) | | `gotica.xml.zip` | [Wulfila Project](https://www.wulfila.be/gothic/download/) | 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](https://github.com/j-luo93/NeuroDecipher) | Full Ugaritic-Hebrew cognate pairs | | `uga-heb.small.no_spe.cog` | [NeuroDecipher](https://github.com/j-luo93/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](https://github.com/j-luo93/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](http://hesperia.ucm.es/en/proyecto_hesperia.php) and cleaned via the authors' Jupyter notebook. ### Linear B / Mycenaean Greek (`data/linear_b/`) | File | Source | Description | |---|---|---| | `linear_b_signs.tsv` | [Unicode UCD](https://www.unicode.org/Public/UCD/latest/) | 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](https://github.com/jhnwnstd/shannon) Linear B Lexicon (MIT, 2,272 entries), [Wiktionary](https://en.wiktionary.org/wiki/Category:Mycenaean_Greek_lemmas) 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](https://github.com/christos-c/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`](cognate_pipeline/README.md) for installation and usage. --- ## Original Repositories - [j-luo93/DecipherUnsegmented](https://github.com/j-luo93/DecipherUnsegmented) — main code for the paper - [j-luo93/NeuroDecipher](https://github.com/j-luo93/NeuroDecipher) — predecessor (Ugaritic/Linear B decipherment) - [j-luo93/xib](https://github.com/j-luo93/xib) — earlier Iberian codebase ## Programmatic Access ### Via HuggingFace `datasets` ```python 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: ```bash pip install git+https://github.com/Project-Phaistos/ancient-scripts-datasets-NEW.git ``` ```python 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](https://github.com/Project-Phaistos/ancient-scripts-datasets-NEW) for full API reference. --- ## Paper Citation ```bibtex @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} } ```