Triple
T649874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pratt & Whitney F135 |
E11321
|
entity |
| Predicate | thrustClass |
P17733
|
FINISHED |
| Object | over 40,000 pounds of thrust with afterburner |
—
|
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: over 40,000 pounds of thrust with afterburner | Statement: [Pratt & Whitney F135, thrustClass, over 40,000 pounds of thrust with afterburner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thrustClass Context triple: [Pratt & Whitney F135, thrustClass, over 40,000 pounds of thrust with afterburner]
-
A.
subclassOf
Indicates that one class is a more specific type of another class, inheriting its characteristics as a subset of it.
-
B.
successorClass
Indicates that one class directly follows or replaces another class in a sequence or hierarchy.
-
C.
UICClassification
Indicates the standardized classification or coding assigned to an entity according to the UIC (International Union of Railways) system.
-
D.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
E.
thesisType
Indicates the specific category or kind of thesis associated with an academic work or degree.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f31e70c81909a2ac1d939f7ec07 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0eade081909c47e85ed55f808d |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49df0de3c81909721eb391ec94031 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.