Triple
T12451954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rexona |
E297552
|
entity |
| Predicate | brandNameUsedInCountry |
P60306
|
FINISHED |
| Object | Sure in the United Kingdom |
—
|
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: Sure in the United Kingdom | Statement: [Rexona, brandNameUsedInCountry, Sure in the United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandNameUsedInCountry Context triple: [Rexona, brandNameUsedInCountry, Sure in the United Kingdom]
-
A.
brandUsedInCountry
chosen
Indicates that a particular brand is used or present within a specified country.
-
B.
usedBrand
Indicates that an entity has utilized, applied, or operated a particular brand in some context.
-
C.
usedInCountry
Indicates that something is utilized, applied, or in operation within the specified country.
-
D.
usedInBrand
Indicates that something (such as a component, material, or element) is utilized as part of or within a particular brand.
-
E.
usedBrandOf
Indicates that one entity made use of or operated an item, product, or service associated with a particular brand.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.