Triple
T21752509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KitKat |
E536948
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | KitKat Chunky |
—
|
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: KitKat Chunky | Statement: [KitKat, hasVariant, KitKat Chunky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KitKat Chunky Context triple: [KitKat, hasVariant, KitKat Chunky]
-
A.
KitKat
chosen
KitKat is a globally popular chocolate-covered wafer bar brand known for its distinctive "Have a break, have a KitKat" slogan and crisp, layered texture.
-
B.
Twix
Twix is a popular chocolate bar consisting of biscuit fingers topped with caramel and coated in milk chocolate, produced and marketed worldwide.
-
C.
New York Super Fudge Chunk
New York Super Fudge Chunk is a rich Ben & Jerry’s ice cream flavor known for its chocolate base packed with fudge chunks, nuts, and other mix-ins.
-
D.
Kit Kat Klub
The Kit Kat Klub is the decadent, Weimar-era Berlin nightclub that serves as the central setting and symbolic backdrop for the musical and film "Cabaret."
-
E.
Snickers
Snickers is a character in the Australian animated children's series "Bluey," known as a dachshund pup who is one of Bluey's friends.
- 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.