Triple
T24791751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daytona Prototype international |
E620268
|
entity |
| Predicate | chassisRegulationBasis |
P122026
|
FINISHED |
| Object | LMP2 chassis |
—
|
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: LMP2 chassis | Statement: [Daytona Prototype international, chassisRegulationBasis, LMP2 chassis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chassisRegulationBasis Context triple: [Daytona Prototype international, chassisRegulationBasis, LMP2 chassis]
-
A.
chassisRegulation
chosen
Indicates that there is a rule or standard governing the design, construction, or use of a chassis in a given context.
-
B.
chassis
Indicates that one entity serves as the structural frame or supporting base (chassis) for another entity.
-
C.
chassisFeature
Indicates that a particular feature, component, or characteristic is part of or associated with a chassis.
-
D.
chassisCode
Indicates the specific chassis designation or code assigned to a vehicle model to distinguish its underlying structural platform or variant.
-
E.
chassisConstruction
Indicates how the chassis of an object is built or assembled, specifying the construction method or structural design used.
- 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_69e2fabe77c8819085f7ce6486248139 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f4110424188190889a13976b16b18a |
completed | May 1, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 4:47 a.m.