Triple
T3851695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | İskender kebap |
E85307
|
entity |
| Predicate | typicalYogurtType |
P51951
|
FINISHED |
| Object | strained yogurt |
—
|
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: strained yogurt | Statement: [İskender kebap, typicalYogurtType, strained yogurt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalYogurtType Context triple: [İskender kebap, typicalYogurtType, strained yogurt]
-
A.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
B.
typicalVariety
Indicates that one entity is a representative or characteristic example of the variety or type defined by another entity.
-
C.
traditionalCheese
Indicates that something is recognized as a cheese made according to established, customary, or historically rooted methods or styles.
-
D.
milkComposition
Indicates the specific nutrients and components that make up a given sample of milk.
-
E.
doughType
Indicates the specific kind or category of dough used or associated with an item or preparation.
- F. None of above. chosen
Provenance (4 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebd0feb081909cc1d5bf41e4acd6 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aee8d9b328819080158be59e5bcc97 |
completed | March 9, 2026, 3:35 p.m. |
Created at: March 9, 2026, 3:19 p.m.