Triple
T12451912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lifebuoy |
E297551
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Lifebuoy Total 10 |
E297551
|
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: Lifebuoy Total 10 | Statement: [Lifebuoy, hasVariant, Lifebuoy Total 10]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lifebuoy Total 10 Context triple: [Lifebuoy, hasVariant, Lifebuoy Total 10]
-
A.
Lifebuoy
chosen
Lifebuoy is a long-established global soap and hygiene brand known for its antibacterial products and health-focused marketing.
-
B.
Brillo
Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
-
C.
Zarvos
Zarvos is a surname most notably associated with Brazilian pianist and film composer Marcelo Zarvos.
-
D.
Colgate Thirteen
Colgate Thirteen is a renowned all-male a cappella group from Colgate University known for performing at high-profile events, including the national anthem at Super Bowl XIII.
-
E.
Crest
Crest is a well-known oral care brand, particularly recognized for its toothpastes and whitening 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.