Triple
T8650775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danbury Municipal Airport |
E205093
|
entity |
| Predicate | supportsPrivateAircraft |
P70100
|
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: [Danbury Municipal Airport, supportsPrivateAircraft, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsPrivateAircraft Context triple: [Danbury Municipal Airport, supportsPrivateAircraft, yes]
-
A.
supportsAircraft
chosen
Indicates that one entity is capable of accommodating, carrying, or enabling the operation of an aircraft.
-
B.
supportsCharterFlights
Indicates that one entity provides the capability or service of operating or accommodating charter flights for another entity.
-
C.
supportsCommercialFlights
Indicates that the subject provides the necessary facilities, services, or conditions for regular commercial passenger or cargo flights to operate.
-
D.
usesCarrierAircraft
Indicates that one entity employs or operates aircraft that are designed to be launched from and recovered by an aircraft carrier.
-
E.
sharesAircraftWith
Indicates that two or more entities use, operate, or are associated with the same aircraft.
- 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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48150e6c8190a7a3b92b4b640858 |
completed | March 31, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69cc45619460819091e83ffdec99c865 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:29 p.m.