Triple
T29744413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McLaren Senna |
E752704
|
entity |
| Predicate | downforceAtSpeed |
P147632
|
FINISHED |
| Object | about 800 kg at 250 km/h |
—
|
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 800 kg at 250 km/h | Statement: [McLaren Senna, downforceAtSpeed, about 800 kg at 250 km/h]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: downforceAtSpeed Context triple: [McLaren Senna, downforceAtSpeed, about 800 kg at 250 km/h]
-
A.
downforceLevel
chosen
Indicates the magnitude of aerodynamic force pressing an object downward, typically enhancing its grip or stability.
-
B.
downforceIncreaseComparedTo
Indicates that one entity experiences a greater amount of aerodynamic downforce than another entity used as a comparison.
-
C.
windResistance
Indicates the degree to which an entity opposes or reduces the effect of wind acting upon it.
-
D.
drivingForce
Indicates a causal influence or motivating factor that propels or significantly shapes another process, event, or outcome.
-
E.
dragCoefficient
Indicates the dimensionless proportionality factor that relates the drag force experienced by an object moving through a fluid to its shape, flow conditions, and reference area.
- 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_69f0d62b064081908c1ae61cd68fb139 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f6736514d88190a856c8f0df03f022 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 7:50 p.m.