Triple
T34060829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexus vehicle platforms |
E873487
|
entity |
| Predicate | usedInModelRange |
P197211
|
FINISHED |
| Object | Lexus sedans |
—
|
NE NERFINISHED |
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: Lexus sedans | Statement: [Lexus vehicle platforms, usedInModelRange, Lexus sedans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInModelRange Context triple: [Lexus vehicle platforms, usedInModelRange, Lexus sedans]
-
A.
usedInDeviceModel
Indicates that something (such as a component, material, or technology) is utilized within or incorporated into a particular device model.
-
B.
usedByModel
Indicates that something (such as a resource, method, or component) is utilized or consumed by a particular model.
-
C.
usedInVersionRange
Indicates that something is applicable, valid, or in effect only within a specified range of versions.
-
D.
useOfModel
Indicates that one entity employs, applies, or relies on a particular model for a specific purpose or task.
-
E.
usesModelsType
Indicates that one entity employs or relies on a specific type or category of models in its operation or behavior.
- F. None of above. chosen
Provenance (4 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_69f349a4af208190afa14888f9c9fb9d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe7bfc94bc81909eeec946e8c1c450 |
completed | May 9, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69fe7b74a1188190886f128e07f712da |
completed | May 9, 2026, 12:10 a.m. |
| PDg | Predicate description generation | batch_69fe7bfb71b08190bed5c33e4ab7afff |
completed | May 9, 2026, 12:12 a.m. |
Created at: May 1, 2026, 1:52 a.m.