Triple
T25021051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 高天原 |
E626568
|
entity |
| Predicate | 関連信仰 |
P102165
|
FINISHED |
| Object | 皇室の神話的起源と結びつく世界 |
—
|
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: 皇室の神話的起源と結びつく世界 | Statement: [高天原, 関連信仰, 皇室の神話的起源と結びつく世界]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連信仰 Context triple: [高天原, 関連信仰, 皇室の神話的起源と結びつく世界]
-
A.
associatedReligionOrBelief
chosen
Indicates that an entity is connected to, identified with, or characterized by a particular religion or belief system.
-
B.
associatedReligionText
Indicates that there is a textual work (such as a scripture or religious document) that is specifically associated with, or pertains to, a given religion.
-
C.
religiousObjectAssociated
Indicates that a religious object is associated with, connected to, or used in relation to another entity (such as a person, place, event, or practice).
-
D.
otherReligion
Indicates that one entity follows or is associated with a religion that is different from the religion of another entity.
-
E.
associatedReligionForRelic
Indicates the religion with which a particular relic is associated.
- 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.