Triple
T11648125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malabo International Airport |
E276828
|
entity |
| Predicate | hasFlightOperationsType |
P18239
|
FINISHED |
| Object | scheduled flights |
—
|
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: scheduled flights | Statement: [Malabo International Airport, hasFlightOperationsType, scheduled flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlightOperationsType Context triple: [Malabo International Airport, hasFlightOperationsType, scheduled flights]
-
A.
hasAircraftOperationsType
Indicates the specific category or type of aircraft operations associated with an entity, such as commercial, military, or private use.
-
B.
aircraftOperationType
Indicates the specific manner or purpose for which an aircraft is being operated (e.g., commercial, private, military, training).
-
C.
hasTypeOfFlights
chosen
Indicates that an entity offers, includes, or is associated with specific categories or kinds of flights.
-
D.
hasRunwayOperations
Indicates that an entity conducts or is involved in operational activities on an airport runway, such as takeoffs, landings, or related ground movements.
-
E.
airlineOperationsType
Indicates the type or category of operational activities an airline conducts (e.g., passenger, cargo, charter, or mixed services).
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a2cd9bb0819093d107204bed2fe0 |
completed | April 10, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d85dd94bdc819091fa2ed33eb31624 |
completed | April 10, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:39 p.m.