Triple
T30435100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chevrolet C5500 |
E774287
|
entity |
| Predicate | commonBodyUpfits |
P194947
|
FINISHED |
| Object | box truck |
—
|
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 | Statement: [Chevrolet C5500, commonBodyUpfits, box truck]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonBodyUpfits Context triple: [Chevrolet C5500, commonBodyUpfits, box truck]
-
A.
typicallyWornWith
Indicates that one item of clothing or accessory is commonly or customarily worn together with another.
-
B.
notableOutfit
Indicates that an entity is known for or associated with wearing a particular outfit or style of clothing.
-
C.
usualAttire
Indicates the type of clothing an entity typically wears in ordinary or characteristic situations.
-
D.
alsoWornIn
Indicates that an item of clothing or accessory is additionally worn in another context, location, or time beyond the primary one mentioned.
-
E.
dressRecommendation
Indicates a suggested or advised choice of dress for a particular person and/or occasion.
- 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_69f22492d2a88190995ce8745d9becaa |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd91a5dad8819093eeeef527027890 |
completed | May 8, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69fd8f65fe9081908902500a3228d935 |
completed | May 8, 2026, 7:23 a.m. |
| PDg | Predicate description generation | batch_69fd91a44268819081b372296e3aa116 |
completed | May 8, 2026, 7:32 a.m. |
Created at: April 29, 2026, 8:07 p.m.