Triple
T22407368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akure South |
E553910
|
entity |
| Predicate | sharesBoundaryWith |
P62639
|
FINISHED |
| Object | Owo |
—
|
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: Owo | Statement: [Akure South, sharesBoundaryWith, Owo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Owo Context triple: [Akure South, sharesBoundaryWith, Owo]
-
A.
Owo
chosen
Owo is a prominent Yoruba sub-group in southwestern Nigeria, known for its rich cultural heritage, traditional art, and historical kingdom centered in present-day Ondo State.
-
B.
Owan
Owan is an ethnic group in southern Nigeria, primarily inhabiting parts of Edo State and known for its distinct language and cultural traditions.
-
C.
Okene
Okene is a major commercial and cultural town in central Nigeria, known for its Ebira-speaking population and strategic location within Kogi State.
-
D.
Oke-Ore
Oke-Ore is a notable town within the Ado-Odo/Ota local government area of Ogun State in southwestern Nigeria.
-
E.
Ojo
Ojo is a central character in L. Frank Baum’s Oz series, notably a Munchkin boy whose quest drives the plot of "The Patchwork Girl of Oz."
- 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158ba1c6481908e4b9b3635ed3a49 |
completed | April 29, 2026, 1:02 a.m. |
Created at: April 16, 2026, 8:46 p.m.