Triple
T30979798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jetstream 41 |
E789331
|
entity |
| Predicate | typicalCruiseSpeedClass |
P9902
|
FINISHED |
| Object | high-subsonic turboprop |
—
|
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: high-subsonic turboprop | Statement: [Jetstream 41, typicalCruiseSpeedClass, high-subsonic turboprop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCruiseSpeedClass Context triple: [Jetstream 41, typicalCruiseSpeedClass, high-subsonic turboprop]
-
A.
cruiseSpeed
Indicates the typical or optimal speed at which an entity is intended to travel under normal operating conditions.
-
B.
aircraftSpeedClass
Indicates the categorical speed range or performance class to which an aircraft’s speed belongs.
-
C.
speedClass
chosen
Indicates the categorical speed level or range assigned to an entity based on how fast it moves or operates.
-
D.
speedClassOfTrains
Indicates the classification of trains based on their operating speed or speed category.
-
E.
supercruiseSpeed
Indicates the speed at which an aircraft or vehicle can sustain supersonic flight without using afterburners or additional boost.
- 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_69f224c4831c8190be53924ec25a150a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:55 p.m.