Triple
T3213453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Harcourt International Airport |
E67334
|
entity |
| Predicate | hasCarHireServices |
P6090
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Port Harcourt International Airport, hasCarHireServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCarHireServices Context triple: [Port Harcourt International Airport, hasCarHireServices, yes]
-
A.
hasRentalCarCenter
chosen
Indicates that a location or facility includes or is associated with a rental car center where vehicles can be rented.
-
B.
hasTaxiStand
Indicates that a location or facility includes or is served by a designated taxi stand area where taxis can wait for passengers.
-
C.
hasBusServices
Indicates that one location or entity is served by bus routes or bus transportation provided by another.
-
D.
hasFuelServices
Indicates that one entity provides or is equipped with fuel-related services or facilities for another entity.
-
E.
hasValet
Indicates that one entity is served or attended by another entity acting as its valet.
- 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_69ad858ac36c81909962589cd277d6e2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaabba8e481909118d9f888ddcd63 |
completed | March 8, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69ad9e09b83881908801d79c3d9254f9 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.