Triple
T34548902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Topolino's Terrace |
E887007
|
entity |
| Predicate | characterDiningFeatures |
P35620
|
FINISHED |
| Object | Mickey Mouse |
—
|
NE NERFINISHED |
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: Mickey Mouse | Statement: [Topolino's Terrace, characterDiningFeatures, Mickey Mouse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterDiningFeatures Context triple: [Topolino's Terrace, characterDiningFeatures, Mickey Mouse]
-
A.
hasCharacterDining
chosen
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
-
B.
hasDiningFeature
Indicates that something possesses a specific characteristic, amenity, or attribute related to dining.
-
C.
diningStyle
Indicates the manner or format in which dining is conducted, such as casual, formal, buffet, or family-style.
-
D.
hasDiningOptionType
Indicates that an entity offers or is associated with a specific type or category of dining option (e.g., dine-in, takeout, delivery).
-
E.
hasDiningComponent
Indicates that something includes or is associated with a dining-related part, feature, or function.
- 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_69f349cff89081908f91e0b064f4833e |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff691f5ae481908597ce245188d31c |
completed | May 9, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69ff67ceeeb081909fd00cad166c4b6a |
completed | May 9, 2026, 4:58 p.m. |
Created at: May 1, 2026, 2:02 a.m.