Triple
T274025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disneyland Resort |
E5206
|
entity |
| Predicate | hasDiningOption |
P4442
|
FINISHED |
| Object | table-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: table-service restaurants | Statement: [Disneyland Resort, hasDiningOption, table-service restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiningOption Context triple: [Disneyland Resort, hasDiningOption, table-service restaurants]
-
A.
hasRestaurant
chosen
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
B.
isServedAt
Indicates that something (such as food, drink, or a service) is provided or made available at a particular place or venue.
-
C.
servesVenue
Indicates that an entity provides services or functions in support of a particular venue.
-
D.
hasSpecialMeal
Indicates that an entity provides, is assigned, or is associated with a designated special meal option.
-
E.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25dd0a99c819089968a5400c58c5f |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7345c4819086c21710864a1b42 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.