Triple
T29431689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McLaren 600LT |
E746448
|
entity |
| Predicate | aerodynamicFeatures |
P19885
|
FINISHED |
| Object | fixed rear wing |
—
|
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: fixed rear wing | Statement: [McLaren 600LT, aerodynamicFeatures, fixed rear wing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aerodynamicFeatures Context triple: [McLaren 600LT, aerodynamicFeatures, fixed rear wing]
-
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.
aircraftDesignFeature
Indicates a relationship where a specific design feature is associated with, or incorporated into, an aircraft.
-
C.
aerodynamicsDerivedFrom
Indicates that the aerodynamic properties or behavior of one entity are obtained, calculated, or inferred based on another entity (such as a model, dataset, or underlying theory).
-
D.
aerodynamicGoal
Indicates a goal or objective specifically related to aerodynamic performance, behavior, or properties in a given context.
-
E.
aerodynamicLoad
Indicates the force or stress exerted on an object due to its interaction with surrounding airflow.
- 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_69f0a7a06e0081908add494075912eb4 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66aca488081909c41adff321b3a48 |
completed | May 2, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 3:13 p.m.