Triple
T34016711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyuto Onsen |
E872266
|
entity |
| Predicate | hasRyokan |
P17960
|
FINISHED |
| Object | Tsurunoyu Onsen |
—
|
NE NERFINISHED |
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: Tsurunoyu Onsen | Statement: [Nyuto Onsen, hasRyokan, Tsurunoyu Onsen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRyokan Context triple: [Nyuto Onsen, hasRyokan, Tsurunoyu Onsen]
-
A.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
B.
hasAccommodation
chosen
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
-
C.
hasGuestHouse
Indicates that one entity owns, includes, or is associated with a guest house in relation to another entity.
-
D.
isResortOf
Indicates that a location or facility functions as a resort associated with, belonging to, or serving a particular entity (such as a city, region, or organization).
-
E.
hasReservationOf
Indicates that one entity holds or possesses a reservation for another entity (such as a service, resource, or event).
- 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_69f349a19ad88190ab586f010c804a8f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70b966860819089cf92927f47c5f1 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70abe43e08190b2a30930d96247c1 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:51 a.m.