Triple
T25021059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 高天原 |
E626568
|
entity |
| Predicate | 神話的地理 |
P20384
|
FINISHED |
| Object | 天の浮橋などと結びつけて語られる |
—
|
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: 天の浮橋などと結びつけて語られる | Statement: [高天原, 神話的地理, 天の浮橋などと結びつけて語られる]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 神話的地理 Context triple: [高天原, 神話的地理, 天の浮橋などと結びつけて語られる]
-
A.
mythologicalLocation
chosen
Indicates that the subject is a place or setting that exists within mythology, legends, or folklore rather than in historical or physical reality.
-
B.
mythologicalSetting
Indicates that an entity is set within, associated with, or takes place in a mythological or legendary context.
-
C.
mythologicalIsland
Indicates that the subject is an island that exists primarily in mythology, legend, or folklore rather than in verified geographic reality.
-
D.
mythologicalContent
Indicates that the subject contains, references, or is associated with myths, mythological narratives, or myth-based elements.
-
E.
mythologicalEvent
Indicates an event or occurrence that takes place within mythological narratives or traditions, often involving gods, heroes, or supernatural phenomena.
- 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_69e2ff28ee3881909c626af002457a4a |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44ba9d564819087d3b9041bb0205b |
completed | May 1, 2026, 6:43 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 6:06 a.m.