Triple
T32970572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Baker & Company |
E843503
|
entity |
| Predicate | usesMarketingImage |
P101201
|
FINISHED |
| Object | La Belle Chocolatière |
—
|
NE NERFINISHED |
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: La Belle Chocolatière | Statement: [Walter Baker & Company, usesMarketingImage, La Belle Chocolatière]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesMarketingImage Context triple: [Walter Baker & Company, usesMarketingImage, La Belle Chocolatière]
-
A.
usedInMarketingMaterials
chosen
Indicates that something is included or featured as part of marketing or promotional materials.
-
B.
hasMarketingElement
Indicates that one entity includes, is associated with, or makes use of a particular marketing-related component or feature.
-
C.
usesImageModel
Indicates that one entity employs or relies on an image-based model (such as a computer vision or image generation model) in relation to another entity or task.
-
D.
hasMarketingTheme
Indicates that an entity is associated with or characterized by a particular marketing theme or campaign concept.
-
E.
hasMarketingIcon
Indicates that an entity is associated with, or represented by, a specific marketing-related icon or symbol.
- 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_69f3494b9fc48190bb61c955ba471275 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 1, 2026, 1:21 a.m.