Triple
T13316638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osaka Marriott Miyako Hotel |
E317203
|
entity |
| Predicate | has24HourFrontDesk |
P59106
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Osaka Marriott Miyako Hotel, has24HourFrontDesk, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has24HourFrontDesk Context triple: [Osaka Marriott Miyako Hotel, has24HourFrontDesk, true]
-
A.
hasFrontDesk
Indicates that one entity provides or is equipped with a front desk service or reception area for another entity.
-
B.
has24HourOperations
chosen
Indicates that an entity operates continuously for 24 hours a day without closing.
-
C.
closedAsHotel
Indicates that an establishment ceased operating in general and specifically stopped functioning as a hotel.
-
D.
hasReservationSystem
Indicates that an entity uses or is equipped with a system for managing reservations or bookings.
-
E.
hasCheckInSystem
Indicates that an entity uses or is equipped with a system for registering or recording check-ins.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6babd88190a5d529df9584b9a4 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:29 p.m.