Triple
T19561683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stronsay Airport |
E489466
|
entity |
| Predicate | supportsMedicalFlights |
P63492
|
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: [Stronsay Airport, supportsMedicalFlights, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsMedicalFlights Context triple: [Stronsay Airport, supportsMedicalFlights, yes]
-
A.
supportsMedEvacOperations
chosen
Indicates the capability or role of providing assistance, resources, or infrastructure necessary to conduct medical evacuation operations.
-
B.
supportsCommercialFlights
Indicates that the subject provides the necessary facilities, services, or conditions for regular commercial passenger or cargo flights to operate.
-
C.
supportsCharterFlights
Indicates that one entity provides the capability or service of operating or accommodating charter flights for another entity.
-
D.
airSupport
Indicates that one entity provides aerial assistance or backing to another, typically through aircraft-based protection, transport, or attack.
-
E.
supportsMedicalSpecialty
Indicates that one entity provides resources, infrastructure, or services that enable or facilitate the practice or development of a particular medical specialty.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f7442e08190ad030151ec0a97d4 |
completed | April 20, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69e514d4df3c8190b7e9b3b4fdf9452a |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:42 p.m.