Triple
T5576482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chevrolet Bel Air (top trim) |
E146330
|
entity |
| Predicate | trimFeatures |
P64540
|
FINISHED |
| Object | additional chrome trim |
—
|
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: additional chrome trim | Statement: [Chevrolet Bel Air (top trim), trimFeatures, additional chrome trim]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trimFeatures Context triple: [Chevrolet Bel Air (top trim), trimFeatures, additional chrome trim]
-
A.
trimLevel
Indicates the specific configuration or package level of features or options applied to an item, typically distinguishing variants within the same base model.
-
B.
featureRemoved
Indicates that a previously existing feature has been taken out, disabled, or is no longer available.
-
C.
cutFormat
Indicates that one entity trims or shapes another entity into a specified format or pattern.
-
D.
cutRule
Indicates that one entity applies or enforces a rule that removes, prunes, or eliminates certain elements or possibilities from consideration.
-
E.
noiseReductionFeature
Indicates that an entity includes or supports a capability to reduce or minimize unwanted noise.
- 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020697fbc8190bd084d7896db3ab8 |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b147cc081909237f3f2967d4cb8 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f0684908190ae2d14f0bd2ab892 |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:37 p.m.