Triple
T23012633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F-body platform |
E572947
|
entity |
| Predicate | usedInBrandLineup |
P4614
|
FINISHED |
| Object | Chevrolet performance cars |
—
|
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: Chevrolet performance cars | Statement: [F-body platform, usedInBrandLineup, Chevrolet performance cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInBrandLineup Context triple: [F-body platform, usedInBrandLineup, Chevrolet performance cars]
-
A.
usedInBrand
Indicates that something (such as a component, material, or element) is utilized as part of or within a particular brand.
-
B.
usedInProductLine
chosen
Indicates that something (such as a component, material, or feature) is utilized within a particular product line.
-
C.
usedOnBrand
Indicates that something (such as a product, material, or element) is applied to, associated with, or utilized in connection with a particular brand.
-
D.
usedBrandOf
Indicates that one entity made use of or operated an item, product, or service associated with a particular brand.
-
E.
brandUsedInCountry
Indicates that a particular brand is used or present within a specified country.
- 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e202a481908d7a2f00a12229a0 |
completed | April 29, 2026, 4:06 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9cd5488190bcd23183179f48cd |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 17, 2026, 3:51 p.m.