Triple
T29706203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McLaren Artura |
E751635
|
entity |
| Predicate | combinedTorque |
P5895
|
FINISHED |
| Object | about 720 Nm |
—
|
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: about 720 Nm | Statement: [McLaren Artura, combinedTorque, about 720 Nm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combinedTorque Context triple: [McLaren Artura, combinedTorque, about 720 Nm]
-
A.
torque
chosen
Indicates a rotational force applied by one entity on another around a pivot or axis.
-
B.
torqueDistribution
Indicates how torque or rotational force is apportioned among multiple components, such as wheels, axles, or motors, within a system.
-
C.
improvedTorqueComparedTo
Indicates that one entity provides greater torque performance than another entity used as a reference.
-
D.
maximumTorque
Indicates the greatest amount of torque that can be produced, transmitted, or withstood in the specified context.
-
E.
torqueCharacteristics
Indicates the relationship between an object and the specific way its torque behaves or varies under different conditions (e.g., speed, load, or operating state).
- 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_69f0d62748848190b030d0a703629a7d |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f672d50f0c8190ba840e7c24470798 |
completed | May 2, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69f6659f246081909821c5f452d14e8f |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 7:27 p.m.