Triple
T1167475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gillette |
E24830
|
entity |
| Predicate | hasSubBrand |
P6092
|
FINISHED |
| Object | Gillette Clinical |
E24830
|
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: Gillette Clinical | Statement: [Gillette, hasSubBrand, Gillette Clinical]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gillette Clinical Context triple: [Gillette, hasSubBrand, Gillette Clinical]
-
A.
Gillette
chosen
Gillette is a globally recognized American brand best known for its razors and shaving products.
-
B.
Listerine
Listerine is a widely used antiseptic mouthwash brand known for its strong flavor and plaque- and germ-fighting oral care products.
-
C.
Braun
Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
-
D.
Suavitel
Suavitel is a popular fabric softener brand known for its long-lasting fragrances and softening properties, marketed primarily in Latin American and U.S. Hispanic households.
-
E.
Colgate-Palmolive
Colgate-Palmolive is a global consumer products company best known for its oral care, personal care, home care, and pet nutrition brands.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bf13ab648190931dea78202096e4 |
completed | March 1, 2026, 10:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac93b6343c8190af6e28ccdaab6562 |
completed | March 7, 2026, 9:08 p.m. |
Created at: March 1, 2026, 7:45 p.m.