Triple
T33983714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chevrolet W-Series |
E871355
|
entity |
| Predicate | typicalUpfits |
P194947
|
FINISHED |
| Object | box truck body |
—
|
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: box truck body | Statement: [Chevrolet W-Series, typicalUpfits, box truck body]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUpfits Context triple: [Chevrolet W-Series, typicalUpfits, box truck body]
-
A.
fashionStyle
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
-
B.
commonBodyUpfits
chosen
Indicates that two or more entities share the same type or configuration of body upfit (e.g., a common body modification or equipment package).
-
C.
fashionFunction
Indicates a relationship where something serves a particular role, purpose, or use within the context of fashion (such as aesthetic, practical, cultural, or symbolic function).
-
D.
dressRecommendation
Indicates a suggested or advised choice of dress for a particular person and/or occasion.
-
E.
notableOutfit
Indicates that an entity is known for or associated with wearing a particular outfit or style of clothing.
- 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:50 a.m.