Triple
T24446411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benetton Group |
E616415
|
entity |
| Predicate | hasCampaignTheme |
P4174
|
FINISHED |
| Object | anti-racism |
—
|
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: anti-racism | Statement: [Benetton Group, hasCampaignTheme, anti-racism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCampaignTheme Context triple: [Benetton Group, hasCampaignTheme, anti-racism]
-
A.
hasMarketingTheme
Indicates that an entity is associated with or characterized by a particular marketing theme or campaign concept.
-
B.
campaignTheme
chosen
Indicates the central idea or message that characterizes and unifies a particular campaign.
-
C.
hasCampaignName
Indicates that an entity is associated with a specific campaign identified by a particular name.
-
D.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
E.
hasThemeInStory
Indicates that a particular theme is present or plays a significant role within a given story.
- 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_69e2d7edca608190aafefc8877a1b4da |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29853a3ac81908bb5398539a44cd6 |
completed | April 29, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:17 a.m.