Triple
T2199078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cobra R |
E50445
|
entity |
| Predicate | aeroFeatures |
P19885
|
FINISHED |
| Object | front splitter |
—
|
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: front splitter | Statement: [Cobra R, aeroFeatures, front splitter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aeroFeatures Context triple: [Cobra R, aeroFeatures, front splitter]
-
A.
aerodynamicsFeature
chosen
Indicates that one entity possesses or is characterized by a specific aerodynamic property, component, or design feature affecting airflow and motion through air.
-
B.
flightDeckFeature
Indicates that one entity is a feature, component, or element that is part of or present on the flight deck of another entity.
-
C.
aircraft
Indicates that an entity is an aircraft or functions in the role of an aircraft in the described context.
-
D.
aircraftConfiguration
Indicates the specific arrangement or setup of an aircraft’s components, systems, or features for a given purpose or operating condition.
-
E.
landingCapability
Indicates the ability or suitability of an entity (e.g., a vehicle or system) to perform a landing under specified conditions.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbf7b65cc8190bcc5a5c52b90f33b |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbda706f4819094de73e1d1d1f539 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.