Triple
T27023404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Airports (Thailand) |
E680723
|
entity |
| Predicate | typeOfAirportOperator |
P34771
|
FINISHED |
| Object | state-owned airport operator |
—
|
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: state-owned airport operator | Statement: [Department of Airports (Thailand), typeOfAirportOperator, state-owned airport operator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfAirportOperator Context triple: [Department of Airports (Thailand), typeOfAirportOperator, state-owned airport operator]
-
A.
aircraftOperator
Indicates that one entity operates, manages, or is responsible for the use of a particular aircraft.
-
B.
belongsToAirportOperator
chosen
Indicates that an airport or related facility is owned, managed, or operated by a specific airport operating organization.
-
C.
servesAsPrimaryAirportOperatorForCity
Indicates that an entity functions as the main organization responsible for operating the primary airport serving a particular city.
-
D.
airlineOperator
Indicates that one entity operates or manages airline services for another entity or in a specified context.
-
E.
airLegOperatedBy
Indicates that a specific segment (leg) of an air journey is operated by a particular airline or carrier.
- 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_69eeeb5450988190bfc9a3c012ac463a |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69fd783fed9c81909e792702636c4f1f |
completed | May 8, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69fd7788e63c81909de22fdafcfe41c0 |
completed | May 8, 2026, 5:41 a.m. |
Created at: April 27, 2026, 7:09 a.m.