Triple
T31755520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Ratatouille (restaurant in the film’s ending) |
E810546
|
entity |
| Predicate | kitchenType |
P17157
|
FINISHED |
| Object | open kitchen |
—
|
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: open kitchen | Statement: [La Ratatouille (restaurant in the film’s ending), kitchenType, open kitchen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: kitchenType Context triple: [La Ratatouille (restaurant in the film’s ending), kitchenType, open kitchen]
-
A.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
B.
cabinetType
Indicates the specific kind or category of cabinet associated with an entity.
-
C.
cuisineFeature
chosen
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
D.
dishType
Indicates the classification of a dish according to its culinary category or role (e.g., appetizer, main course, dessert).
-
E.
heatingMethod
Indicates the method or technique used to apply heat to something, such as for cooking, warming, or processing.
- 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_69f348e340d48190b780fae618c51464 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca3dedc81908b519d53d2909868 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 30, 2026, 11:29 p.m.