Triple
T3943836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Innocent Drinks |
E92096
|
entity |
| Predicate | hasMarketingApproach |
P48415
|
FINISHED |
| Object | ethical branding |
—
|
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: ethical branding | Statement: [Innocent Drinks, hasMarketingApproach, ethical branding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarketingApproach Context triple: [Innocent Drinks, hasMarketingApproach, ethical branding]
-
A.
hasMarketingTheme
chosen
Indicates that an entity is associated with or characterized by a particular marketing theme or campaign concept.
-
B.
hasMarketingChannel
Indicates that an entity utilizes or is associated with a particular marketing channel for promotion or communication.
-
C.
hasMarketingCategory
Indicates that an entity is associated with a specific marketing category or segment used for classification or targeting.
-
D.
hasMarketingRole
Indicates that an entity holds a position or responsibility related to marketing activities within an organization.
-
E.
marketingAs
Indicates that one entity is being presented, promoted, or branded to others as if it were another specified entity, role, or category.
- 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_69aed965502c8190904ebad1203a4ae8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee764235081909309b3c982f322a9 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:24 p.m.