Triple
T24226934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Be the One |
E601621
|
entity |
| Predicate | labelMarketingRole |
P155272
|
FINISHED |
| Object | introduced Dua Lipa to international markets |
—
|
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: introduced Dua Lipa to international markets | Statement: [Be the One, labelMarketingRole, introduced Dua Lipa to international markets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelMarketingRole Context triple: [Be the One, labelMarketingRole, introduced Dua Lipa to international markets]
-
A.
labelMarketingPositioning
Indicates that an entity defines or assigns the marketing positioning (how something is presented or positioned in the market) for another entity.
-
B.
labelMarketingFocus
Indicates that something is designated as the primary marketing focus or emphasis within a given context.
-
C.
labelMarketingConcept
Indicates that something is designated or identified as a specific marketing concept.
-
D.
hasMarketingRole
Indicates that an entity holds a position or responsibility related to marketing activities within an organization.
-
E.
labelOf
Indicates that one entity serves as the name, tag, or identifying label assigned to another entity.
- 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_69e29538aafc8190a2386fdebbd1393b |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f287dffa6c81908564b74dbfae780b |
completed | April 29, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69f1c448abec8190b87cbf9ed419a309 |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f1c6d4e99081909f61899eccafb73e |
completed | April 29, 2026, 8:52 a.m. |
Created at: April 18, 2026, 12:01 a.m.