Triple
T8630971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A3ST |
E204399
|
entity |
| Predicate | aircraftMarketSegment |
P55881
|
FINISHED |
| Object | specialized transport |
—
|
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: specialized transport | Statement: [A3ST, aircraftMarketSegment, specialized transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftMarketSegment Context triple: [A3ST, aircraftMarketSegment, specialized transport]
-
A.
airlineMarket
Indicates a commercial air transport relationship where an airline provides or operates flight services within a specific origin–destination market or route.
-
B.
airlineMarketSegment
chosen
Indicates a relationship where an airline is associated with a specific market segment it targets or operates within (e.g., business, leisure, regional).
-
C.
typicalAircraftTypeCategory
Indicates the general class or category of aircraft type that is most commonly associated with or used in a given context.
-
D.
avionicsSupplier
Indicates that one entity supplies avionics systems, components, or related services to another entity.
-
E.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
- 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:27 p.m.