Triple
T32135496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ShishKebab |
E820754
|
entity |
| Predicate | cuisineOfOrigin |
P133695
|
FINISHED |
| Object | Middle Eastern cuisine |
—
|
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: Middle Eastern cuisine | Statement: [ShishKebab, cuisineOfOrigin, Middle Eastern cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cuisineOfOrigin Context triple: [ShishKebab, cuisineOfOrigin, Middle Eastern cuisine]
-
A.
placeOfOrigin
Indicates the location or source from which an entity originally comes or was created.
-
B.
originCountryCuisine
Indicates that a cuisine originates from or is traditionally associated with a particular country.
-
C.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
D.
hasCulinaryOrigin
chosen
Indicates that something originates from, or is traditionally associated with, a particular culinary tradition, cuisine, or food culture.
-
E.
countryOfOrigin
Indicates the country from which an entity originally comes or was first produced, created, or established.
- 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_69f349039e0c819091c7a7d322e3f46d |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b9a9bc4c8190a88918fc4f91136a |
completed | May 3, 2026, 2:57 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a970b0819090c6473844ffa8e3 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:30 a.m.