Triple
T21752447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nescafé |
E536947
|
entity |
| Predicate | hasProductVariant |
P455
|
FINISHED |
| Object | Nescafé Gold |
—
|
NE NERFINISHED |
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: Nescafé Gold | Statement: [Nescafé, hasProductVariant, Nescafé Gold]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nescafé Gold Context triple: [Nescafé, hasProductVariant, Nescafé Gold]
-
A.
Nescafé
chosen
Nescafé is a globally popular brand of instant coffee and related coffee products owned by Nestlé.
-
B.
Sanka Coffie
Sanka Coffie is the laid-back, humorous pushcart driver and brakeman who provides comic relief and heart in the Jamaican bobsled team in the film "Cool Runnings."
-
C.
Coffee-Mate
Coffee-Mate is a popular non-dairy coffee creamer brand known for its wide variety of flavored and powdered creamers used to enhance coffee.
-
D.
Lavazza
Lavazza is a major Italian coffee company renowned worldwide for its espresso blends and coffee products.
-
E.
Lipton
Lipton is a globally recognized tea brand offering a wide range of tea products, including black, green, and herbal varieties.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d8b8b9c8190b1f6a8bc25d69dbb |
completed | April 28, 2026, 2:38 a.m. |
Created at: April 16, 2026, 6:50 p.m.