Triple
T33778077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Endo |
E865575
|
entity |
| Predicate | ethnicallyEquivalentTo |
P111282
|
FINISHED |
| Object | Marakwet people |
—
|
NE NERFINISHED |
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: Marakwet people | Statement: [Endo, ethnicallyEquivalentTo, Marakwet people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethnicallyEquivalentTo Context triple: [Endo, ethnicallyEquivalentTo, Marakwet people]
-
A.
equivalentEthnonym
chosen
Indicates that two different ethnonyms refer to the same ethnic group or people.
-
B.
isEthnonymFor
Indicates that one term is the ethnonym (name of a people or ethnic group) used to refer to another entity.
-
C.
nearEthnicGroup
Indicates that one entity is located geographically close to an ethnic group.
-
D.
commonInEthnicGroup
Indicates that something (such as a trait, condition, or characteristic) occurs with notable frequency within a specified ethnic group.
-
E.
relatedEthnonymNote
Indicates that there is an explanatory note describing how this ethnonym is related to another ethnonym or term.
- 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fccdd496048190bca801a8a9eecb62 |
completed | May 7, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 1, 2026, 1:45 a.m.