Triple
T3864656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buick Envision |
E91821
|
entity |
| Predicate | trimLevelExamples |
P11486
|
FINISHED |
| Object | Preferred |
—
|
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: Preferred | Statement: [Buick Envision, trimLevelExamples, Preferred]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trimLevelExamples Context triple: [Buick Envision, trimLevelExamples, Preferred]
-
A.
trimLevel
chosen
Indicates the specific configuration or package level of features or options applied to an item, typically distinguishing variants within the same base model.
-
B.
levels
Indicates that one entity adjusts, equalizes, or smooths out the height, intensity, or degree of another entity.
-
C.
representationLevel
Indicates the degree or layer at which something stands in for, models, or symbolizes something else (e.g., more concrete vs. more abstract representation).
-
D.
representedLevel
Indicates that one entity denotes or encodes the degree, intensity, or value (i.e., the level) of another entity or property.
-
E.
coversLevel
Indicates that one entity includes or encompasses a particular level or layer of another entity or system.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec3a253c81909df7dc0422ff7989 |
completed | March 9, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69aee754dddc8190936e1f9c40a770db |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.