Triple
T13088361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T134 |
E310394
|
entity |
| Predicate | hasEngineMounting |
P92607
|
FINISHED |
| Object | rear-fuselage-mounted engines |
—
|
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: rear-fuselage-mounted engines | Statement: [T134, hasEngineMounting, rear-fuselage-mounted engines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEngineMounting Context triple: [T134, hasEngineMounting, rear-fuselage-mounted engines]
-
A.
hasMountingFeature
Indicates that one entity includes or provides a structural feature intended for mounting or attaching another entity.
-
B.
hasMount
Indicates that an entity is equipped with, riding, or otherwise using another entity as a mount for transportation or support.
-
C.
aircraftEngineMounting
chosen
Indicates that an aircraft engine is attached or secured to a supporting structure or mounting point on the aircraft.
-
D.
hasEngineProgram
Indicates that an entity is associated with or participates in a specific engine-related program.
-
E.
engineTypeUsed
Indicates that a particular type of engine is employed or utilized in relation to a specified entity or system.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d98138a1d481908a139f2f67eb3472 |
completed | April 10, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69d9803f6c508190bfadfbc2d00c2c64 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:02 p.m.