Triple
T15649121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gillett |
E376258
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Gillette |
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 | Statement: [Gillett, hasVariant, Gillette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gillette Context triple: [Gillett, hasVariant, Gillette]
-
A.
Gillette
chosen
Gillette is a globally recognized American brand best known for its razors and shaving products.
-
B.
Gilette
Gilette is a small French commune in the Alpes-Maritimes department of southeastern France, known for its hilltop setting overlooking the confluence of the Var and Estéron rivers.
-
C.
Braun
Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
-
D.
Colgate
Colgate is a small village in West Sussex, England, known for its rural character and proximity to Horsham.
-
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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed7212c8190be6ff76afa25f7ca |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff67957ebc8190b187f557bd01d58d |
completed | May 9, 2026, 4:57 p.m. |
Created at: April 10, 2026, 4:15 a.m.