Triple
T10952357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenmore Air seaplane base |
E258754
|
entity |
| Predicate | aircraftTypeHandled |
P1524
|
FINISHED |
| Object | floatplane |
—
|
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: floatplane | Statement: [Kenmore Air seaplane base, aircraftTypeHandled, floatplane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftTypeHandled Context triple: [Kenmore Air seaplane base, aircraftTypeHandled, floatplane]
-
A.
aircraftType
chosen
Indicates the specific model or category of aircraft associated with an entity or event.
-
B.
aircraftTypeMaintained
Indicates that a maintenance entity performs or is responsible for maintaining a specific type of aircraft.
-
C.
supportsAircraft
Indicates that one entity is capable of accommodating, carrying, or enabling the operation of an aircraft.
-
D.
usedByAircraftType
Indicates that something (such as equipment, infrastructure, or a procedure) is employed or operated by a specific type or category of aircraft.
-
E.
appliesToAircraftFamily
Indicates that a rule, condition, or characteristic is relevant to, or valid for, an entire family or series of related aircraft models.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770fcfb3c8190b7823869670184a6 |
completed | April 9, 2026, 9:27 a.m. |
| PD | Predicate disambiguation | batch_69d72e874f48819096ffa878f90c7d5b |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:23 p.m.