Triple
T26227806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rampuri kebabs |
E655943
|
entity |
| Predicate | usesSpices |
P44787
|
FINISHED |
| Object | garam masala |
—
|
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: garam masala | Statement: [Rampuri kebabs, usesSpices, garam masala]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSpices Context triple: [Rampuri kebabs, usesSpices, garam masala]
-
A.
typicalSpices
Indicates that certain spices are commonly or characteristically used in association with a particular dish, cuisine, or ingredient.
-
B.
hasSpice
chosen
Indicates that one entity contains, includes, or is characterized by a particular spice or set of spices.
-
C.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
D.
usesIngredientInfluenceFrom
Indicates that one entity incorporates or applies the influence, properties, or effects derived from a particular ingredient in its action or outcome.
-
E.
hasSpiciness
Indicates that one entity possesses a certain level or quality of spiciness in relation to another entity or a defined scale.
- 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_69ee5b4b8b408190993da38c0067cc8d |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 26, 2026, 8:58 p.m.