Triple
T1749961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pratt & Whitney F117-PW-100 |
E38416
|
entity |
| Predicate | thrustReverser |
P24153
|
FINISHED |
| Object | equipped |
—
|
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: equipped | Statement: [Pratt & Whitney F117-PW-100, thrustReverser, equipped]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thrustReverser Context triple: [Pratt & Whitney F117-PW-100, thrustReverser, equipped]
-
A.
thrustVectorControl
Indicates the capability to direct or adjust the direction of thrust from a propulsion system to control an object's attitude or trajectory.
-
B.
landingGear
Indicates that an entity’s landing gear is present, deployed, or otherwise involved in a landing-related state or action relative to another entity or context.
-
C.
thrustAtSeaLevel
Indicates the amount of propulsive force an engine produces when operating at standard sea-level atmospheric conditions.
-
D.
propulsionFeature
chosen
Indicates a relationship where a propulsion-related characteristic or capability is attributed to an entity.
-
E.
thrustInVacuum_kN
Indicates the amount of propulsive force an engine produces in a vacuum, measured in kilonewtons.
- 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_69a8862bdb2081908aefe831c8aa8017 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba6a63f588190b53b39c6b97d74f4 |
completed | March 7, 2026, 4:16 a.m. |
| PD | Predicate disambiguation | batch_69aa61c7ef4c8190abec87c96a787d82 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.