Triple
T12795741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yewa North |
E305884
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object | Ayetoro |
E1001996
|
NE 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: Ayetoro | Statement: [Yewa North, hasMajorTown, Ayetoro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ayetoro Context triple: [Yewa North, hasMajorTown, Ayetoro]
-
A.
Ayetoro
chosen
Ayetoro is a prominent town in Ogun State, southwestern Nigeria, serving as a local commercial and cultural center.
-
B.
Atessa
Atessa is a town and municipality in the Abruzzo region of central Italy, known for its industrial activity and automotive manufacturing facilities.
-
C.
Aytos
Aytos is a small town in southeastern Bulgaria known as an administrative and economic center within Burgas Province.
-
D.
Noresco
Noresco is an energy services and performance contracting company known for developing and implementing energy efficiency and infrastructure modernization projects.
-
E.
Oetari
Oetari was the first wife of Sukarno (born Kusno Sosrodihardjo), Indonesia’s future first president.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e6db68481909a2ca8da1287f3e0 |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ec0d5dc819099a8036c6cbac634 |
completed | May 2, 2026, 11:54 p.m. |
Created at: April 9, 2026, 5:30 p.m.