Triple
T12296064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ibom Air |
E293088
|
entity |
| Predicate | hasFocusCity |
P1295
|
FINISHED |
| Object | Enugu |
E82541
|
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: Enugu | Statement: [Ibom Air, hasFocusCity, Enugu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enugu Context triple: [Ibom Air, hasFocusCity, Enugu]
-
A.
Enugu
chosen
Enugu is a major city in southeastern Nigeria known historically for its coal mining industry and role as a regional administrative and economic center.
-
B.
Owerri
Owerri is the capital and largest city of Imo State in southeastern Nigeria, known as a regional cultural and commercial center.
-
C.
Onitsha
Onitsha is a major commercial and river port city on the eastern bank of the Niger River in southeastern Nigeria, known for its large open-air market and vibrant trade.
-
D.
Makurdi
Makurdi is the capital city of Benue State in central Nigeria, serving as an important administrative and commercial hub in the region.
-
E.
Nnewi
Nnewi is a major commercial and industrial city in southeastern Nigeria, renowned for its vibrant automotive parts manufacturing and trade.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93ed903808190b7ed90e0db3d7586 |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64b8cf0e8819088f5ee03495bbf61 |
completed | May 2, 2026, 7:07 p.m. |
Created at: April 8, 2026, 9:52 p.m.