Triple
T18024977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akagi mountain lakes |
E431221
|
entity |
| Predicate | isScenicSpot |
P118718
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Akagi mountain lakes, isScenicSpot, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isScenicSpot Context triple: [Akagi mountain lakes, isScenicSpot, yes]
-
A.
isScenicArea
Indicates that a location is recognized as a scenic area, typically valued for its natural beauty or visually appealing surroundings.
-
B.
isScenicStopOn
chosen
Indicates that a location serves as a designated scenic viewpoint or attraction situated along a particular route or path.
-
C.
isPartOfScenicVista
Indicates that something is included within, or contributes to, a larger scenic vista or panoramic view.
-
D.
isScenicTown
Indicates that a town is visually attractive or picturesque, often due to its natural surroundings, architecture, or overall aesthetic appeal.
-
E.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9c554348190bd0df06d0cfe188e |
completed | April 19, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:24 a.m.