Triple
T14713768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deji of Akure |
E345621
|
entity |
| Predicate | associatedWithCity |
P1481
|
FINISHED |
| Object | Akure |
E131420
|
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: Akure | Statement: [Deji of Akure, associatedWithCity, Akure]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akure Context triple: [Deji of Akure, associatedWithCity, Akure]
-
A.
Akure
chosen
Akure is the capital city of Ondo State in southwestern Nigeria, known as an important administrative and commercial center in the region.
-
B.
Aulestad
Aulestad is the historic Norwegian country estate and museum best known as the longtime home of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
-
C.
Sandvika
Sandvika is a town in southeastern Norway that serves as the administrative center of Bærum and a commercial hub in the Greater Oslo Region.
-
D.
Esteio
Esteio is a municipality in the state of Rio Grande do Sul in southern Brazil, known for its industrial activity and for hosting one of the country’s major agricultural fairs.
-
E.
Alerheim
Alerheim is a small municipality in the Donau-Ries district of Bavaria in southern Germany.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb98513b081908b230f6ac79c72ad |
completed | April 14, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe24a996708190834733bfc669c3d3 |
completed | May 8, 2026, 6 p.m. |
Created at: April 10, 2026, 1:29 a.m.