Triple
T4460017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rolls-Royce Pegasus |
E98227
|
entity |
| Predicate | nozzleDeflectionRange |
P56663
|
FINISHED |
| Object | approximately 0 to 98 degrees |
—
|
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: approximately 0 to 98 degrees | Statement: [Rolls-Royce Pegasus, nozzleDeflectionRange, approximately 0 to 98 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nozzleDeflectionRange Context triple: [Rolls-Royce Pegasus, nozzleDeflectionRange, approximately 0 to 98 degrees]
-
A.
nozzleExpansionRatio
Indicates the ratio between a nozzle’s exit area and its throat area, describing how much the flow expands as it passes through the nozzle.
-
B.
numberOfNozzles
Indicates the quantity of nozzles associated with or present on a given entity.
-
C.
propellantRatio
Indicates the proportional relationship between different propellant components used together in a propulsion system.
-
D.
combustionChamber
Indicates that one entity functions as the combustion chamber in which another entity’s fuel–air mixture is burned to produce energy or propulsion.
-
E.
thrustInVacuum_kN
Indicates the amount of propulsive force an engine produces in a vacuum, measured in kilonewtons.
- F. None of above. chosen
Provenance (4 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_69b3454a7c608190944f5455c8031d73 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35673337c8190b923159791ec27e3 |
completed | March 13, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69b34f649df081909d3cc2f6a1b8f282 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b354e1f0948190b645096b2b7037af |
completed | March 13, 2026, 12:05 a.m. |
Created at: March 12, 2026, 11:33 p.m.