Triple
T15645912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scoops |
E376175
|
entity |
| Predicate | isPartOfBrand |
P6092
|
FINISHED |
| Object | Tostitos brand portfolio |
E77118
|
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: Tostitos brand portfolio | Statement: [Scoops, isPartOfBrand, Tostitos brand portfolio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tostitos brand portfolio Context triple: [Scoops, isPartOfBrand, Tostitos brand portfolio]
-
A.
Tostitos
chosen
Tostitos is a popular American brand of tortilla chips and related snack foods produced by Frito-Lay.
-
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.
TACO
TACO is a peer-reviewed scientific journal published by the ACM that focuses on research in computer architecture and code optimization.
-
E.
Taco Bell
Taco Bell is a major American fast-food chain known for its Mexican-inspired menu items such as tacos, burritos, and quesadillas.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed5b8b081908d7127964eed3b09 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6790f2288190add8ab0bc0f114bf |
completed | May 9, 2026, 4:57 p.m. |
Created at: April 10, 2026, 4:15 a.m.