Triple
T12451943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rexona |
E297552
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Rexona Clinical Protection |
E297552
|
NE 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: Rexona Clinical Protection | Statement: [Rexona, hasVariant, Rexona Clinical Protection]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rexona Clinical Protection Context triple: [Rexona, hasVariant, Rexona Clinical Protection]
-
A.
Rexona
chosen
Rexona is a global deodorant and antiperspirant brand known for its long-lasting sweat and odor protection products.
-
B.
Dettol
Dettol is a widely used antiseptic and disinfectant brand known for its germ-killing cleaning and personal hygiene products.
-
C.
Lysol
Lysol is a well-known brand of household disinfectant and cleaning products widely used for sanitizing surfaces and killing germs.
-
D.
Febreze
Febreze is a popular household odor-eliminating product line known for its air fresheners and fabric refreshers.
-
E.
Listerine
Listerine is a widely used antiseptic mouthwash brand known for its strong flavor and plaque- and germ-fighting oral care products.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d94d9fa5f0819080ca9f6efa212c59 |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f16e87c8190b7e9f61561ae865a |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:56 p.m.