Triple
T4033780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mallam Aminu Kano International Airport |
E83777
|
entity |
| Predicate | namedForNationalityOfEponym |
P17299
|
FINISHED |
| Object | Nigerian |
—
|
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 | Statement: [Mallam Aminu Kano International Airport, namedForNationalityOfEponym, Nigerian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForNationalityOfEponym Context triple: [Mallam Aminu Kano International Airport, namedForNationalityOfEponym, Nigerian]
-
A.
namedForNationality
chosen
Indicates that something is named after or in reference to a particular nationality or national identity.
-
B.
eponymCountry
Indicates that a country is named after (or serves as the namesake for) a particular person, place, or entity.
-
C.
namedForNationalityOfHonouree
Indicates that something is named in honor of a person, specifically referencing that person's nationality.
-
D.
ethnicEponymOf
Indicates that one term is an eponym derived from or naming an ethnic group or people.
-
E.
hasEponymCitizenship
Indicates that an entity’s eponym (the person or figure it is named after) holds or held a particular citizenship or national affiliation.
- F. None of above.
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_69aed92e29ac819080f7a98b594fec05 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb108fc0819080c8f41da2e558e0 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fe440c819093a7fa22c4ff3f1a |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:36 p.m.