Triple
T19839575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Antonio International Airport |
E476688
|
entity |
| Predicate | aircraftOperationsType |
P92236
|
FINISHED |
| Object | commercial airline |
—
|
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: commercial airline | Statement: [San Antonio International Airport, aircraftOperationsType, commercial airline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftOperationsType Context triple: [San Antonio International Airport, aircraftOperationsType, commercial airline]
-
A.
aircraftOperationType
chosen
Indicates the specific manner or purpose for which an aircraft is being operated (e.g., commercial, private, military, training).
-
B.
hasAircraftOperationsType
Indicates the specific category or type of aircraft operations associated with an entity, such as commercial, military, or private use.
-
C.
airlineOperationsType
Indicates the type or category of operational activities an airline conducts (e.g., passenger, cargo, charter, or mixed services).
-
D.
aircraftTypesOperated
Indicates the types or models of aircraft that an entity (such as an airline or operator) uses or operates.
-
E.
servesAviationType
Indicates that one entity provides services or functions specifically for a particular type or category of aviation.
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65804be608190b49e110c3bf381bc |
completed | April 20, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.