Triple
T8272747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ottoman cuisine |
E193467
|
entity |
| Predicate | notableDessert |
P8416
|
FINISHED |
| Object | baklava |
—
|
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: baklava | Statement: [Ottoman cuisine, notableDessert, baklava]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableDessert Context triple: [Ottoman cuisine, notableDessert, baklava]
-
A.
pastryType
Indicates the specific kind or category of pastry that an item belongs to.
-
B.
traditionalSweet
chosen
Indicates that something is a sweet food or dessert prepared according to long-established customs or cultural traditions.
-
C.
notableMeatProduct
Indicates that one entity is a meat-based product that is especially prominent, well-known, or significant in relation to the other entity.
-
D.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
E.
traditionalDish
Indicates that the object is a dish customarily prepared, eaten, or recognized within the subject’s cultural or regional tradition.
- 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_69ca82e14ae481908ffdb822cd2192bc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb798878988190a5f63c854aa070f2 |
completed | March 31, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69cb70a4525481909399d313a6247ace |
completed | March 31, 2026, 6:58 a.m. |
Created at: March 30, 2026, 5:50 p.m.