Datasets:
Update DATABASE_REFERENCE with ACD stats
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docs/DATABASE_REFERENCE.md
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# Ancient Scripts Datasets — Master Database Reference
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> **Last updated:** 2026-03-14 | **
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This document is the single source of truth for understanding, modifying, and extending this database. It is designed for both human researchers and AI agents.
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- 3,466,000+ total lexical entries
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- 170,756 ancient language entries (68 languages)
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- 3,296,156 modern language entries (1,113 languages)
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### Cognate Pairs (v2)
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| File | Rows | Description |
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|------|------|-------------|
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| `cognate_pairs_inherited.tsv` |
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| `cognate_pairs_borrowing.tsv` | 17,147 | Verified donor→recipient borrowings from WOLD BorrowingTable |
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| `cognate_pairs_similarity.tsv` | 465,233 | Algorithmic phonetic similarity: concept_aligned (219,519, score ≥ 0.5) + similarity_only (245,714, 0.3 ≤ score < 0.5) |
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**Sources & provenance:**
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- **ABVD** CognateTable (20,697,739 pairs, 1,682 Austronesian languages) — Expert-classified by Greenhill, Blust & Gray (2008). Sister-sister relationships within cognate sets. `loan_flagged` for 160,768 pairs where ABVD Loan column non-empty.
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- **IE-CoR** CognateTable (365,913 pairs, 159 Indo-European languages) — Expert-classified by Heggarty et al. (2023, Science). Mixed PIE-level (32%) and branch-level (55%) cognacy. `loan_involved` for 3,598 pairs where cognateset appears in loans.csv.
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- **Sino-Tibetan** CognateTable (4,166 pairs) — Expert-classified from STEDT-derived data (Jacques & List). Borrowings (146 entries) pre-filtered at extraction.
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- **WOLD** BorrowingTable (17,147 pairs) — Expert borrowing judgments from Haspelmath & Tadmor (2009). `borrowed_immediate` (13,967) vs `borrowed_earlier` (3,180). Score = -1 sentinel for pseudo-IPA entries. Entries with "no evidence for borrowing" (802) filtered out.
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# Ancient Scripts Datasets — Master Database Reference
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> **Last updated:** 2026-03-14 | **Total entries:** 3,466,000+ across 1,178 languages
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This document is the single source of truth for understanding, modifying, and extending this database. It is designed for both human researchers and AI agents.
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|
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| 125 |
- 3,466,000+ total lexical entries
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| 126 |
- 170,756 ancient language entries (68 languages)
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| 127 |
- 3,296,156 modern language entries (1,113 languages)
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- 23,375,899 cognate/borrowing/similarity pairs
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### Cognate Pairs (v2)
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| File | Rows | Description |
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|------|------|-------------|
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| `cognate_pairs_inherited.tsv` | 22,893,519 | Expert-classified cognates ONLY (ABVD + ACD + IE-CoR + Sino-Tibetan) |
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| `cognate_pairs_borrowing.tsv` | 17,147 | Verified donor→recipient borrowings from WOLD BorrowingTable |
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| `cognate_pairs_similarity.tsv` | 465,233 | Algorithmic phonetic similarity: concept_aligned (219,519, score ≥ 0.5) + similarity_only (245,714, 0.3 ≤ score < 0.5) |
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**Sources & provenance:**
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- **ABVD** CognateTable (20,697,739 pairs, 1,682 Austronesian languages) — Expert-classified by Greenhill, Blust & Gray (2008). Sister-sister relationships within cognate sets. `loan_flagged` for 160,768 pairs where ABVD Loan column non-empty.
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- **ACD** Cognacy groups (1,825,701 pairs, 727 Austronesian languages) — Expert-classified by Blust, Trussel & Smith (2023), DOI: 10.5281/zenodo.7737547. Cross-language pairs within cognacy groups. Score = -1 for all (no reliable IPA; pseudo-IPA from orthography). `loan_flagged` for 573 pairs where ACD Loan column is True.
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- **IE-CoR** CognateTable (365,913 pairs, 159 Indo-European languages) — Expert-classified by Heggarty et al. (2023, Science). Mixed PIE-level (32%) and branch-level (55%) cognacy. `loan_involved` for 3,598 pairs where cognateset appears in loans.csv.
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| 148 |
- **Sino-Tibetan** CognateTable (4,166 pairs) — Expert-classified from STEDT-derived data (Jacques & List). Borrowings (146 entries) pre-filtered at extraction.
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- **WOLD** BorrowingTable (17,147 pairs) — Expert borrowing judgments from Haspelmath & Tadmor (2009). `borrowed_immediate` (13,967) vs `borrowed_earlier` (3,180). Score = -1 sentinel for pseudo-IPA entries. Entries with "no evidence for borrowing" (802) filtered out.
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