Triple
T105211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian Market |
E2123
|
entity |
| Predicate | cuisineType |
P5786
|
FINISHED |
| Object | Italian 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: Italian cuisine | Statement: [Italian Market, cuisineType, Italian cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cuisineType Context triple: [Italian Market, cuisineType, Italian cuisine]
-
A.
traditionalCuisine
Indicates that an entity is associated with the customary or historically rooted style of cooking and food preparation characteristic of a particular culture, region, or community.
-
B.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
C.
placeOfOrigin
Indicates the location or source from which an entity originally comes or was created.
-
D.
feast
Indicates that an entity participates in or hosts a large, elaborate meal or celebration involving abundant food and communal dining.
-
E.
diet
Indicates that an entity regularly consumes a particular type or range of food as its primary source of nutrition.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a25711f6788190a22252ea3a3af394 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563be81c81908ccc5ed44edd6b8e |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2570f45bc81909ebba7ee5f602976 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.