Triple
T6896715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 佳子内親王 |
E159387
|
entity |
| Predicate | 宗教的背景 |
P9028
|
FINISHED |
| Object | 神道（皇室の伝統的信仰） |
—
|
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: 神道（皇室の伝統的信仰） | Statement: [佳子内親王, 宗教的背景, 神道（皇室の伝統的信仰）]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 宗教的背景 Context triple: [佳子内親王, 宗教的背景, 神道（皇室の伝統的信仰）]
-
A.
religiousCulturalContext
chosen
Indicates the religious or cultural setting, tradition, or framework within which an entity, practice, or event occurs or is interpreted.
-
B.
religiousFoundation
Indicates that an entity was established, created, or founded by a religious organization, authority, or tradition.
-
C.
religiousBackgroundOfBase
Indicates the religious background or affiliation associated with a given base or primary entity.
-
D.
hasReligiousOrigin
Indicates that something originates from, is derived from, or is fundamentally based on a religious tradition, belief system, or practice.
-
E.
religiousCharacteristic
Indicates that one entity has a religious attribute, quality, or affiliation that characterizes or distinguishes it in a religious context.
- 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_69c6883822e0819091e321526f20ae0a |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d95ae3f88190b7f5d440f90ae9f9 |
completed | March 27, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b7681481909ec50509b19fcf81 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:24 p.m.