Triple
T6093282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Street (Canada's Wonderland) |
E135816
|
entity |
| Predicate | hasFoodOption |
P68068
|
FINISHED |
| Object | quick-service restaurants |
—
|
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: quick-service restaurants | Statement: [International Street (Canada's Wonderland), hasFoodOption, quick-service restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFoodOption Context triple: [International Street (Canada's Wonderland), hasFoodOption, quick-service restaurants]
-
A.
hasMealType
Indicates that an entity is associated with a specific category or type of meal (such as breakfast, lunch, or dinner).
-
B.
hasStapleFood
Indicates that an entity’s primary or regularly consumed basic food item is another specified entity.
-
C.
hasSpecialMeal
Indicates that an entity provides, is assigned, or is associated with a designated special meal option.
-
D.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
-
E.
foodItem
Indicates that one entity is a food item that can be eaten or used as food in relation to another entity.
- 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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057ac8c7481909fb22cf157be45ce |
completed | March 22, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69c049f3b1ec8190bea67a7bec6442a5 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8e3f2c8190be459ca02f9b315a |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:12 p.m.