Triple
T13692051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sakura |
E328289
|
entity |
| Predicate | hasOnboardFacilities |
P12416
|
FINISHED |
| Object | reserved seating |
—
|
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: reserved seating | Statement: [Sakura, hasOnboardFacilities, reserved seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnboardFacilities Context triple: [Sakura, hasOnboardFacilities, reserved seating]
-
A.
hasGoodsFacilities
Indicates that a location or entity is equipped with facilities for handling, storing, or processing goods or cargo.
-
B.
hasFacilities
chosen
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
C.
hasBackstageFacilities
Indicates that a venue or location provides backstage areas and related facilities for performers or staff.
-
D.
hasMaintenanceFacilities
Indicates that one entity provides or contains facilities where the other entity can be serviced, repaired, or maintained.
-
E.
basedOnFacility
Indicates that something is determined, derived, or decided according to the characteristics, rules, or conditions of a particular facility.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8746458819095ec1ba3c01ef31b |
completed | April 12, 2026, 4:29 p.m. |
| PD | Predicate disambiguation | batch_69dbbe9059488190a8113177c83e1481 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:53 p.m.