Triple
T3213464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Harcourt International Airport |
E67334
|
entity |
| Predicate | hasAircraftParkingStands |
P13763
|
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, hasAircraftParkingStands, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAircraftParkingStands Context triple: [Port Harcourt International Airport, hasAircraftParkingStands, yes]
-
A.
hasBoardingGatesFor
Indicates that a location or facility provides designated boarding gates used for embarking passengers onto specific transportation services (such as flights or trains).
-
B.
aircraftFacility
chosen
Indicates that a facility is designed, equipped, or used to support the operation, maintenance, or accommodation of aircraft.
-
C.
hasStationAtAirport
Indicates that an organization or service operates a station or facility located at a specific airport.
-
D.
airportStation
Indicates a location functions as an airport facility where air transport operations occur.
-
E.
hasHangars
Indicates that one entity possesses or contains hangars used for housing aircraft or similar vehicles.
- 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.