Triple
T2296241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Redmond Municipal Airport |
E51620
|
entity |
| Predicate | supportsGeneralAviation |
P24735
|
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: [Redmond Municipal Airport, supportsGeneralAviation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsGeneralAviation Context triple: [Redmond Municipal Airport, supportsGeneralAviation, yes]
-
A.
hasGeneralAviationFacilities
chosen
Indicates that a location or airport provides facilities and services specifically for general aviation operations.
-
B.
supportsWideBodyAircraft
Indicates that an entity (such as an airport, runway, or gate) is capable of accommodating and handling wide-body aircraft operations.
-
C.
aviationUsage
Indicates that something is used for, involved in, or associated with aviation-related activities or purposes.
-
D.
supportsNarrowBodyAircraft
Indicates that one entity is capable of accommodating, servicing, or being compatible with narrow-body aircraft.
-
E.
usedInAviation
Indicates that something is employed or applied within the field or context 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcd0e42248190ada33b84d75caa64 |
completed | March 7, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69abc589295c819092989820c2b4e9d8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.