Triple
T2677525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Egba |
E56494
|
entity |
| Predicate | hasCulturalLanguageVariant |
P5595
|
FINISHED |
| Object | Egba dialect of Yoruba |
—
|
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: Egba dialect of Yoruba | Statement: [Egba, hasCulturalLanguageVariant, Egba dialect of Yoruba]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCulturalLanguageVariant Context triple: [Egba, hasCulturalLanguageVariant, Egba dialect of Yoruba]
-
A.
languageVariant
chosen
Indicates that one language is a variant, dialect, or localized form of another language.
-
B.
isCulturalLanguageOf
Indicates that a language serves as a primary medium of cultural expression, identity, and heritage for a particular group, community, or region.
-
C.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
D.
hasRegionalVariationsIn
Indicates that something exhibits different forms, versions, or characteristics depending on the geographic region.
-
E.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
- 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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abda2f7bf88190a1e3103dd014d871 |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd81ab9d08190b72b6104c6dbc769 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.