Triple
T18087593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TAG Farnborough Airport Ltd |
E432876
|
entity |
| Predicate | airportTypeOperated |
P86085
|
FINISHED |
| Object | business aviation airport |
—
|
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: business aviation airport | Statement: [TAG Farnborough Airport Ltd, airportTypeOperated, business aviation airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportTypeOperated Context triple: [TAG Farnborough Airport Ltd, airportTypeOperated, business aviation airport]
-
A.
airportTypeManaged
Indicates that an entity is responsible for managing or overseeing a particular type or category of airport.
-
B.
servesAsPrimaryAirportOperatorForCity
Indicates that an entity functions as the main organization responsible for operating the primary airport serving a particular city.
-
C.
operatesAirport
Indicates that one entity manages and runs the operations of an airport.
-
D.
airlineOperationsType
Indicates the type or category of operational activities an airline conducts (e.g., passenger, cargo, charter, or mixed services).
-
E.
airportTypePresent
chosen
Indicates that a specific type or category of airport is present or exists in relation to the referenced entity.
- 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dd16234c8190b547e893a829d6c5 |
completed | April 19, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69e4330e1f2881908b2506d47c48736b |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:27 a.m.