Triple
T2719094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nnamdi Azikiwe International Airport |
E60037
|
entity |
| Predicate | isNamedAfterOccupation |
P41835
|
FINISHED |
| Object | Nigerian nationalist leader |
—
|
LITERAL 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: Nigerian nationalist leader | Statement: [Nnamdi Azikiwe International Airport, isNamedAfterOccupation, Nigerian nationalist leader]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNamedAfterOccupation Context triple: [Nnamdi Azikiwe International Airport, isNamedAfterOccupation, Nigerian nationalist leader]
-
A.
namesakeOccupation
Indicates that one entity’s occupation is the same as, or derived from, the occupation associated with the other entity’s namesake.
-
B.
isOccupationalSurname
Indicates that a surname originates from or is derived from a person’s occupation or trade.
-
C.
hasPlaceNamedAfter
Indicates that one place is named in honor of or derived from the name of another place.
-
D.
nameGivesRiseTo
Indicates that one name, term, or designation leads to, causes, or results in the emergence or establishment of another.
-
E.
hasAwardNamedAfter
Indicates that an entity has an award that is named in honor of another entity.
- F. None of above. chosen
Provenance (4 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_69ab4b746d248190958e052045c09255 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdaaee104819085966bc54d5da9c0 |
completed | March 7, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69abd8240920819087a812d816a55edb |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd949c120819099a9d56eb71a0339 |
completed | March 7, 2026, 7:52 a.m. |
Created at: March 6, 2026, 9:55 p.m.