Triple
T1332464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ndyuka language |
E28673
|
entity |
| Predicate | primaryLexifier |
P3083
|
FINISHED |
| Object | English language |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: English language | Statement: [Ndyuka language, primaryLexifier, English language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryLexifier Context triple: [Ndyuka language, primaryLexifier, English language]
-
A.
primaryLexifierLanguage
chosen
Indicates the main source language from which the core vocabulary and structure of another language, typically a contact or creole language, are primarily derived.
-
B.
primaryName
Indicates that the associated name is the main or most commonly used name for the entity in question.
-
C.
primaryGrammaticalBasis
Indicates that one element serves as the main grammatical foundation or core structure upon which another linguistic element is based or constructed.
-
D.
primaryReference
Indicates that one entity serves as the main or authoritative source of information or citation for another entity.
-
E.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1e7f1388190a6e4eb65a7997380 |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.