Triple
T19424320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago-style hot dogs |
E485938
|
entity |
| Predicate | typicalPepperType |
P56695
|
FINISHED |
| Object | pickled sport peppers |
—
|
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: pickled sport peppers | Statement: [Chicago-style hot dogs, typicalPepperType, pickled sport peppers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPepperType Context triple: [Chicago-style hot dogs, typicalPepperType, pickled sport peppers]
-
A.
typicalSpices
Indicates that certain spices are commonly or characteristically used in association with a particular dish, cuisine, or ingredient.
-
B.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
C.
hasSpiciness
Indicates that one entity possesses a certain level or quality of spiciness in relation to another entity or a defined scale.
-
D.
isTypicallyGarnishedWith
chosen
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
E.
typicalVariety
Indicates that one entity is a representative or characteristic example of the variety or type defined by 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63217bd2c81909e216e13aa4c487d |
completed | April 20, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.