Triple
T27809959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Café Orleans |
E702490
|
entity |
| Predicate | hasTableServiceWaitstaff |
P166854
|
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: [Café Orleans, hasTableServiceWaitstaff, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTableServiceWaitstaff Context triple: [Café Orleans, hasTableServiceWaitstaff, yes]
-
A.
hasBarService
Indicates that one entity provides or features bar service for another entity or at a given location.
-
B.
hasRoomService
Indicates that a lodging or accommodation offers room service as an available amenity or feature.
-
C.
crewServed
Indicates that the operation or use of something requires a coordinated effort by multiple people acting together as a crew.
-
D.
hasSectionServed
Indicates that an entity has a specific section or portion that has been served or provided.
-
E.
hasWaitingArea
Indicates that an entity provides or includes a designated space where people can wait before receiving a service or proceeding to another area.
- F. None of above. chosen
Provenance (4 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_69ef840a16748190926719ab96120bae |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f664aa283c8190a869d0555eff60c6 |
completed | May 2, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f663362c008190a22afed262f1e426 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f6645a615481909b53d94512ecbaf1 |
completed | May 2, 2026, 8:53 p.m. |
Created at: April 27, 2026, 5:41 p.m.