Triple
T10831137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Topolino's Terrace – Flavors of the Riviera |
E255619
|
entity |
| Predicate | hasSignatureDishes |
P17971
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Topolino's Terrace – Flavors of the Riviera, hasSignatureDishes, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignatureDishes Context triple: [Topolino's Terrace – Flavors of the Riviera, hasSignatureDishes, yes]
-
A.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
B.
hasSpecialtyFood
chosen
Indicates that an entity offers, serves, or is associated with a particular type of specialty food.
-
C.
hasDishType
Indicates that an item (such as a food or menu entry) is classified as belonging to a particular type of dish (e.g., appetizer, main course, dessert).
-
D.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
-
E.
haveCuisine
Indicates that an entity (such as a restaurant or place) offers, serves, or is associated with a particular type or style of cuisine.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d744222288819093258b452569acab |
completed | April 9, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69d70d25280c8190b648d7d1958b413a |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:19 p.m.