Version: 0.12 Date: 2026-05-22 Status: Complete — Sprint 4.2 deliverable
This specification defines the format, sourcing strategy, and expansion plan for the Nested Semantic Graph (NSG) cross-linguistic corpus. The corpus provides empirical ground truth for validating the central claim of "Few Become One" (DOI: 10.5281/zenodo.20328374): that diverse surface languages linearize the same Nested Semantic Tree — an ultrametric structure invariant under translation.
The project corpus (0.9.py, build_expanded_corpus()) contains 12 documents across 5 languages:
| Language | Type | Count | Documents |
|---|---|---|---|
| English | Isolating | 6 | EN-1 through EN-6 |
| Turkish | Agglutinative | 2 | TR-1, TR-2 |
| Mohawk | Polysynthetic | 1 | MH-1 |
| Finnish | Agglutinative | 2 | FI-1, FI-2 |
| Inuktitut | Polysynthetic | 1 | IK-1 |
All 12 share 1-2 core propositions (DOG-BITE-MAN), built from hand-crafted semantic trees. All pass ultrametric verification (0 violations).
Limitations:
- Small (12 documents) — insufficient for quantitative claims
- Narrow propositional coverage (predominantly DOG-BITE-MAN)
- Hand-crafted trees, not parsed from real text
- No pre-existing parallel corpus used
The expansion target by project close-out (S4.4) is 25+ documents:
| Requirement | Current | Target |
|---|---|---|
| Total documents | 12 | 25+ |
| Languages | 5 | 8+ |
| Language families | 3 (IE, Turkic, Eskimo-Aleut) | 5+ |
| Proposition clusters | 2 | 5+ |
| Ultrametric verification | 100% pass | 100% pass |
Each corpus entry is a (doc_id, sentence, gloss, english, language, source, tree_spec) tuple defined as follows:
| Field | Type | Required | Description |
|---|---|---|---|
doc_id |
string | Yes | Unique identifier: {LANG}-{N} (e.g., "JA-1") |
sentence |
string | Yes | Surface sentence in source language (UTF-8, native script) |
gloss |
string | Yes | Morpheme-by-morpheme gloss in English (Leipzig Glossing Rules) |
english |
string | Yes | Natural English translation |
language |
string | Yes | Language name (English) |
source |
enum | Yes | Origin: HAND-CRAFTED, PARALLEL-TEXT, UD-TREEBANK, FIELDWORK, GRAMMAR |
tree_spec |
dict | Yes | NST construction specification (see §4.2) |
iso_639 |
string | — | ISO 639-3 language code (e.g., "tur", "moh") |
family |
string | — | Language family (e.g., "Turkic", "Iroquoian") |
typology |
enum | — | Morphological type: ISOLATING, AGGLUTINATIVE, POLYSYNTHETIC, FUSIONAL |
proposition_cluster |
string | — | Semantic grouping (e.g., "TRANSFER-OBJECT", "MOTION-PATH") |
source_ref |
string | — | Citation or URL for source text |
notes |
string | — | Linguist's notes on interesting features |
The tree_spec dict encodes how the surface sentence maps to an NST:
tree_spec = {
"root": "S", # Root node category
"verb": { # Verb phrase
"stem": "bit", # Verb root lemma
"category": "BITE", # Semantic category
"tense": "PAST", # TAM marking
"voice": "ACTIVE", # Voice
},
"participants": [ # Ordered argument list
{"role": "AGENT", "stem": "dog", "category": "ANIMAL"},
{"role": "PATIENT", "stem": "man", "category": "HUMAN"},
],
"adjuncts": [ # Optional modifiers
{"type": "TEMPORAL", "stem": "yesterday"},
{"type": "LOCATIVE", "stem": "park"},
{"type": "INSTRUMENTAL", "stem": "stick"},
],
"morphology": { # Language-specific encoding
"case_marking": "NOM-ACC", # or "ERG-ABS", "DIRECT-INVERSE"
"agreement": "SUBJ", # Agreement target
"incorporation": False, # Noun incorporation?
}
}# Corpus entries as list of tuples
CORPUS_ENTRY = (
doc_id: str, # "JA-1"
sentence: str, # "Inu ga kino otoko o kanda"
gloss: str, # "dog NOM yesterday man ACC bit"
english: str, # "The dog bit the man yesterday"
language: str, # "Japanese"
source: str, # "PARALLEL-TEXT"
tree_spec: dict, # See §4.2
_meta: dict # Optional: {iso_639, family, typology, cluster, ref, notes}
)URL: https://universaldependencies.org/ Access: Free, open-source (CC BY-SA 4.0) Size: 200+ treebanks, 100+ languages Relevance: UD provides dependency parses with universal POS tags and dependency relations. The dependency tree can be transformed into an NST by mapping universal relations to semantic roles.
Mapping strategy:
| UD Relation | NST Role |
|---|---|
nsubj |
AGENT (if active) / PATIENT (if passive) |
obj / iobj |
PATIENT / RECIPIENT |
obl |
ADJUNCT (LOCATIVE, TEMPORAL, INSTRUMENTAL) |
root (VERB) |
VERB_PHRASE root |
Recommended treebanks for NSG:
- English (EWT, GUM) — isolating baseline
- Turkish (IMST, BOUN) — agglutinative
- Finnish (TDT) — agglutinative
- Japanese (GSD) — SOV, postpositional
- Hindi (HDTB) — split-ergative
- Arabic (PADT) — non-concatenative morphology
- Basque (BDT) — ergative-absolutive
- Warlpiri (if available) — non-configurational
Limitation: UD trees capture syntactic dependencies, NOT semantic roles directly. NST requires semantic role mapping, which adds a manual step.
URL: https://github.com/christos-c/bible-corpus Access: Free, public domain Size: 1,600+ languages, ~7,000 verse-aligned translations Relevance: The most extensive parallel corpus available. Every verse has translations in hundreds of languages, providing natural parallel data for NST isomorphism verification.
Recommended verses for NSG:
- Genesis 1:1-3 (creation — causal chain)
- Exodus 3:14 (being — existential)
- Psalm 23:1-3 (shepherd — benefactive)
- John 1:1 (logos — equative)
- Matthew 5:3-5 (blessed — attributive)
Advantage: Guaranteed semantic parallelism — all translations encode the same proposition. Limitation: Biblical language is formal/archaic. May not reflect natural spoken language structures.
URL: https://wals.info/ Access: Free, open-access Size: 192 structural features, 2,600+ languages Relevance: WALS provides typological features for language selection, ensuring the corpus spans diverse morphological and syntactic types. NOT a text corpus — used for language sampling, not document sourcing.
Features relevant to NSG sampling:
| WALS Feature | Relevance |
|---|---|
| 20A: Fusion of inflectional formatives | Morphological type (isolating → polysynthetic) |
| 49A: Number of cases | Case marking richness |
| 81A: Order of Subject, Object, Verb | Word order — affects linearization |
| 98A: Alignment of case marking | Nominative-accusative vs ergative-absolutive |
| 101A: Expression of pronominal subjects | Pro-drop parameter |
| 102A: Verbal person marking | Agreement morphology |
| 104A: Order of possessor and possessum | Genitive construction |
Sampling strategy: Select 2 languages from each of the 5 major morphological types (isolating, agglutinative, fusional, polysynthetic, introflexive), ensuring at least one non-Indo-European per type.
| Resource | Type | Relevance |
|---|---|---|
| ODIN (Online Database of Interlinear Text) | Glossed text | Pre-glassed examples from linguistic field manuals |
| Tatoeba | Parallel sentences | Community-contributed translations in 400+ languages |
| CMU Pronouncing Dictionary | Phonological | Not directly relevant to NST |
| Ethnologue | Language catalog | ISO codes, family classification |
| Glottolog | Language catalog | Comprehensive classification with references |
Add documents covering new proposition clusters:
| Cluster | Example Proposition | Target Languages |
|---|---|---|
| TRANSFER-OBJECT | "The woman gave the book to the child" | English, Turkish, Finnish, Japanese, Hindi |
| MOTION-PATH | "The man went from the house to the store" | English, Turkish, Mohawk |
| PERCEPTION | "The child saw the dog in the garden" | English, Finnish, Inuktitut |
| CAUSATIVE | "The woman made the child eat" | Turkish, Japanese (causative morphology) |
| BENEFACTIVE | "The man baked bread for the woman" | English, Mohawk (applicative) |
Add 3 new languages with 2 documents each:
| Language | Family | Type | Source |
|---|---|---|---|
| Japanese | Japonic | Agglutinative (SOV) | UD-GSD treebank |
| Basque | Isolate | Ergative-absolutive | UD-BDT treebank |
| Swahili | Bantu | Agglutinative (noun class) | Grammar-based |
Add 3 documents from the Parallel Bible:
| Verse | Languages | Proposition |
|---|---|---|
| Genesis 1:1 | English, Turkish, Mohawk | "God created the heavens and the earth" |
| Psalm 23:1 | English, Finnish, Inuktitut | "The Lord is my shepherd" |
| John 1:1 | English, Japanese | "In the beginning was the Word" |
Each new corpus entry MUST pass:
- Lexical coverage: Every morpheme in
tree_spechas a corresponding entry in the language's LEXICON - Tree construction:
build_nst_from_morphology()produces a valid tree with ≥2 leaves - Ultrametric property: All triples of leaf nodes satisfy the strong triangle inequality (0 violations)
- Isomorphism check: Documents in the same proposition cluster share isomorphic tree structure (same node count, same category hierarchy, same leaf ordering up to linearization)
| File | Purpose |
|---|---|
0.12.md |
This specification |
0.12.py |
Corpus loader and format validator (optional, for S4.3 integration) |
0.9.py |
Expanded corpus implementation (existing, target expansion) |
- Real Zemberek? The Turkish pipeline (0.10.py) simulates Zemberek output. Should S4.3-S4.4 attempt actual Zemberek integration? Decision: NOT in this sprint. Simulation is sufficient for prototype.
- UD dependency → NST mapping: The mapping is non-trivial (syntax ≠ semantics). Should we implement a rule-based mapper? Decision: Manual tree specification for key examples, automated mapper as future spinoff.
- Publication scope: Should the corpus spec be included in the final publication (0.7.md)? Decision: Yes — as §3 (Methodology) appendix.
- Few Become One (DOI: 10.5281/zenodo.20328374) — Core paper on ultrametric language architecture
- Language as Information Architecture (DOI: 10.5281/zenodo.20137616) — Quantitative foundation
- Universal Dependencies: https://universaldependencies.org/
- WALS: https://wals.info/
- Parallel Bible Corpus: https://github.com/christos-c/bible-corpus
- Leipzig Glossing Rules: https://www.eva.mpg.de/lingua/resources/glossing-rules.php