Triple
T16329527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mapo |
E396512
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Oyo State |
—
|
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: Oyo State | Statement: [Mapo, locatedIn, Oyo State]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oyo State Context triple: [Mapo, locatedIn, Oyo State]
-
A.
Oyo State
chosen
Oyo State is a southwestern Nigerian state historically known as the heartland of the old Oyo Empire and a major center of Yoruba culture and politics.
-
B.
Osun State
Osun State is a southwestern Nigerian state that is a cultural and historical heartland of the Yoruba people, known for its traditional festivals and religious heritage.
-
C.
Ogun State
Ogun State is a southwestern Nigerian state known as a key Yoruba cultural heartland and an important industrial and educational hub.
-
D.
Ondo State
Ondo State is a coastal state in southwestern Nigeria known for its oil-producing areas, diverse ethnic communities, and significant role within the Niger Delta region.
-
E.
Ekiti State
Ekiti State is a landlocked, predominantly Yoruba-speaking state in southwestern Nigeria known for its hilly terrain and strong emphasis on education.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4ddc5608190b24fe2e871691470 |
completed | April 17, 2026, 11:40 p.m. |
Created at: April 10, 2026, 5:07 a.m.