Triple
T3638059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tostitos |
E77118
|
entity |
| Predicate | flavorVariety |
P41829
|
FINISHED |
| Object | Original Restaurant Style |
—
|
LITERAL 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: Original Restaurant Style | Statement: [Tostitos, flavorVariety, Original Restaurant Style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flavorVariety Context triple: [Tostitos, flavorVariety, Original Restaurant Style]
-
A.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
B.
varietyOf
chosen
Indicates that one entity is a specific type, kind, or variant of another, more general entity.
-
C.
hasApproximateNumberOfVarieties
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
-
D.
typicalVariety
Indicates that one entity is a representative or characteristic example of the variety or type defined by another entity.
-
E.
colorVarietyOf
Indicates that one entity represents a specific color variant or color option of another entity.
- F. None of above.
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_69ad85dd0be48190b738990cb20c4731 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc328e5e481909d26318c743bc84a |
completed | March 8, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69adb842be7c8190b7dfdb7c906f294c |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.