Triple
T6757465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bunka no Hi |
E154498
|
entity |
| Predicate | typicalLocationOfEvents |
P49732
|
FINISHED |
| Object | museums in Japan |
—
|
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: museums in Japan | Statement: [Bunka no Hi, typicalLocationOfEvents, museums in Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLocationOfEvents Context triple: [Bunka no Hi, typicalLocationOfEvents, museums in Japan]
-
A.
typicalOnsetLocation
Indicates the anatomical location where a condition, symptom, or process most commonly begins or first appears.
-
B.
locationOfEventDescribed
chosen
Indicates that one entity is the place or setting where the event described by another entity occurs.
-
C.
eventLocationOfNotableActivity
Indicates that a location is the place where a notable or significant activity or event involving the related entity occurred.
-
D.
typicalEvent
Indicates that the associated event is a common, characteristic, or prototypical occurrence for the given entity or situation.
-
E.
typicalUseLocation
Indicates the usual or most common location where an entity is used or operates.
- 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d327e37081909d576e6eff9eec97 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09227108190b253b91967831a85 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:11 p.m.