Triple
T36605307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Be Our Guest Restaurant |
E903028
|
entity |
| Predicate | currentServiceModel |
P152613
|
FINISHED |
| Object | prix fixe menu |
—
|
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: prix fixe menu | Statement: [Be Our Guest Restaurant, currentServiceModel, prix fixe menu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentServiceModel Context triple: [Be Our Guest Restaurant, currentServiceModel, prix fixe menu]
-
A.
providesServiceModel
chosen
Indicates that one entity supplies or makes available a particular service model for use by another entity.
-
B.
currentServicePatternIntroduced
Indicates that the currently operating service pattern was first implemented or put into effect at a specific point in time.
-
C.
clientServiceModel
Indicates a relationship where a particular service model is provided, managed, or applied for a given client.
-
D.
currentSupport
Indicates that one entity is presently providing assistance, backing, or resources to another.
-
E.
usesLiveServiceModel
Indicates that an entity operates based on or interacts with a live, continuously running service model rather than a static or offline model.
- 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_69f76e66b7b88190848f7a3e1188915f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff956dc6548190979171d4b4068d47 |
completed | May 9, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69ff93dc39c481908a97a12c3ef7dfe7 |
completed | May 9, 2026, 8:06 p.m. |
Created at: May 3, 2026, 4:11 p.m.