Triple
T10190302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casino Rama Resort |
E238014
|
entity |
| Predicate | hasFineDiningRestaurant |
P4442
|
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: [Casino Rama Resort, hasFineDiningRestaurant, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFineDiningRestaurant Context triple: [Casino Rama Resort, hasFineDiningRestaurant, yes]
-
A.
isDiningDestination
Indicates that a place serves as a destination where people go specifically to eat meals or dine.
-
B.
hasRestaurant
chosen
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
C.
hasRestaurantType
Indicates that an entity is associated with or classified as a particular type or category of restaurant.
-
D.
hasCharacterDining
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
-
E.
hasDiningFeature
Indicates that something possesses a specific characteristic, amenity, or attribute related to dining.
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded7d6fdc81908052866495b6574f |
completed | April 2, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69cd7c8477648190bc55c56aeec507d3 |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:13 p.m.