Triple
T11841207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cutlass Supreme |
E281655
|
entity |
| Predicate | becameStandaloneModel |
P72840
|
FINISHED |
| Object | 1970 model year |
—
|
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: 1970 model year | Statement: [Cutlass Supreme, becameStandaloneModel, 1970 model year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becameStandaloneModel Context triple: [Cutlass Supreme, becameStandaloneModel, 1970 model year]
-
A.
becameStandaloneModelYear
chosen
Indicates the year in which an entity first transitioned into being recognized or produced as an independent, standalone model.
-
B.
isStandaloneFriendly
Indicates that an entity can operate or be used effectively on its own without requiring integration or support from other entities.
-
C.
adoptedModel
Indicates that one entity has formally chosen, accepted, or implemented another entity as its preferred model or standard.
-
D.
standardizedModel
Indicates that an entity conforms to a defined, uniform model or specification used as a standard across multiple instances or contexts.
-
E.
introducedAsModel
Indicates that one entity is presented or identified to others in the role or capacity of a model.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a658f918819092c2db05fe2ab0ce |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a254a57481908a1e6ad97919c416 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.