Triple
T22918391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lay's |
E568791
|
entity |
| Predicate | hasProductVariant |
P455
|
FINISHED |
| Object | Lay's Wavy |
—
|
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: Lay's Wavy | Statement: [Lay's, hasProductVariant, Lay's Wavy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lay's Wavy Context triple: [Lay's, hasProductVariant, Lay's Wavy]
-
A.
Lay's
chosen
Lay's is a globally popular brand of potato chips known for its wide variety of flavors and mass-market snack appeal.
-
B.
Pringles
Pringles is a popular brand of stackable potato-based crisps known for their uniform curved shape and distinctive cylindrical can packaging.
-
C.
The Pringles
The Pringles are a snobbish, influential family who serve as key antagonists to Anne Shirley in L.M. Montgomery’s novel "Anne of Windy Poplars."
-
D.
Cheez-It
Cheez-It is a popular American snack brand known for its small, square, cheese-flavored crackers.
-
E.
Wheat Thins
Wheat Thins are a popular brand of thin, crispy whole-grain wheat crackers commonly eaten as a snack or with dips and cheese.
- 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.