Triple
T30786082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 岐阜県美術館 |
E783958
|
entity |
| Predicate | 開館種別 |
P38211
|
FINISHED |
| Object | 公立文化施設 |
—
|
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: 公立文化施設 | Statement: [岐阜県美術館, 開館種別, 公立文化施設]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 開館種別 Context triple: [岐阜県美術館, 開館種別, 公立文化施設]
-
A.
isCulturalInstitutionOf
Indicates that an entity functions as a cultural institution belonging to, serving, or associated with another entity (such as a place, community, or organization).
-
B.
hasCulturalFacilityType
chosen
Indicates that an entity has or is associated with a specific type of cultural facility (such as a museum, theater, or gallery).
-
C.
isPublicMuseum
Indicates that an institution operates as a museum that is open and accessible to the general public, typically under public or non-profit ownership or management.
-
D.
libraryCollectionType
Indicates the specific category or type of collection that a library maintains or offers (e.g., reference, circulating, digital).
-
E.
hasMuseumType
Indicates that an entity is classified as a museum of a specific type or category.
- 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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f690097c9c81909858e7d8c15474da |
completed | May 3, 2026, midnight |
| PD | Predicate disambiguation | batch_69f686140aa08190a35f62572b2db9b6 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:41 p.m.