Triple
T11634275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oba of Lagos |
E276475
|
entity |
| Predicate | religiousFunctions |
P2330
|
FINISHED |
| Object | custodian of Yoruba deities in Lagos |
—
|
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: custodian of Yoruba deities in Lagos | Statement: [Oba of Lagos, religiousFunctions, custodian of Yoruba deities in Lagos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousFunctions Context triple: [Oba of Lagos, religiousFunctions, custodian of Yoruba deities in Lagos]
-
A.
religiousFunction
chosen
Indicates that one entity serves a religious role, purpose, or function in relation to another entity.
-
B.
religiousActivity
Indicates participation in, performance of, or association with practices, rituals, or behaviors related to a religion or faith tradition.
-
C.
religiousEvent
Indicates that an event is related to religious practices, observances, or ceremonies.
-
D.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
E.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
- 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a25c0b00819095898d2b2445ecfb |
completed | April 10, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69d85dd94bdc819091fa2ed33eb31624 |
completed | April 10, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:39 p.m.