Triple
T21751915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gingembre Rouge |
E536934
|
entity |
| Predicate | hasPackagingTheme |
P61999
|
FINISHED |
| Object | red color scheme |
—
|
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: red color scheme | Statement: [Gingembre Rouge, hasPackagingTheme, red color scheme]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPackagingTheme Context triple: [Gingembre Rouge, hasPackagingTheme, red color scheme]
-
A.
hasMarketingTheme
Indicates that an entity is associated with or characterized by a particular marketing theme or campaign concept.
-
B.
packagingStyle
Indicates the manner or format in which a product or item is packaged or presented.
-
C.
colorOfPackaging
Indicates the color attribute associated with the packaging of an item or product.
-
D.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
E.
hasThemingDetail
chosen
Indicates that something includes or is associated with a specific thematic element, motif, or stylistic detail.
- 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d8a6d4881908cc69e7247cce3a5 |
completed | April 28, 2026, 2:38 a.m. |
| PD | Predicate disambiguation | batch_69e6969c16fc8190b5126c169317d85d |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:50 p.m.