Triple
T22918293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PEP |
E568789
|
entity |
| Predicate | hasUnderlyingBrandPortfolio |
P99659
|
FINISHED |
| Object | Cheetos |
—
|
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: Cheetos | Statement: [PEP, hasUnderlyingBrandPortfolio, Cheetos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cheetos Context triple: [PEP, hasUnderlyingBrandPortfolio, Cheetos]
-
A.
Cheetos
chosen
Cheetos is a popular brand of cheese-flavored puffed corn snacks known for their bright orange color and crunchy texture.
-
B.
Doritos
Doritos is a popular brand of flavored tortilla chips known for its bold, intense seasonings and triangular shape.
-
C.
Fritos
Fritos is a popular American brand of crunchy corn chips known for its distinctive salty flavor and use in snacks like Frito pie.
-
D.
Cheez-It
Cheez-It is a popular American snack brand known for its small, square, cheese-flavored crackers.
-
E.
Pringles
Pringles is a popular brand of stackable potato-based crisps known for their uniform curved shape and distinctive cylindrical can packaging.
- 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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1807b254c8190bb84596dcacaa35e |
completed | April 29, 2026, 3:52 a.m. |
Created at: April 17, 2026, 3:42 p.m.