Triple
T21887477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 玉依姫 |
E540442
|
entity |
| Predicate | 関連宗教 |
P27867
|
FINISHED |
| Object | 神道 |
—
|
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 | Statement: [玉依姫, 関連宗教, 神道]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連宗教 Context triple: [玉依姫, 関連宗教, 神道]
-
A.
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.
-
B.
associatedReligionOrBelief
Indicates that an entity is connected to, identified with, or characterized by a particular religion or belief system.
-
C.
otherReligion
Indicates that one entity follows or is associated with a religion that is different from the religion of another entity.
-
D.
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).
-
E.
hasAssociatedReligion
chosen
Indicates that an entity is connected with or linked to a particular religion.
- 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_69e0c47a95908190ae3e19b716accb3d |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f118ed35948190bbffba2c40029eee |
completed | April 28, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69e6be9a65888190a66598d62d20366c |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 7:05 p.m.