Triple
T17737814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsukiyomi Shrine |
E442768
|
entity |
| Predicate | hasAssociatedReligionBranch |
P27867
|
FINISHED |
| Object | Shintoism in Kyushu region |
—
|
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: Shintoism in Kyushu region | Statement: [Tsukiyomi Shrine, hasAssociatedReligionBranch, Shintoism in Kyushu region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedReligionBranch Context triple: [Tsukiyomi Shrine, hasAssociatedReligionBranch, Shintoism in Kyushu region]
-
A.
hasAssociatedReligion
chosen
Indicates that an entity is connected with or linked to a particular religion.
-
B.
religiousBranchOf
Indicates that one religion, denomination, or sect is a subdivision or offshoot of a larger parent religious tradition.
-
C.
hasReligiousType
Indicates that an entity is associated with or classified under a particular religion or religious category.
-
D.
hasEponymReligion
Indicates that a religion is named after or derived from the name of a particular person.
-
E.
hasReligiousInstitutionType
Indicates that an entity is associated with, or classified by, a specific type of religious institution.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47aca27448190943c75e723ceefcc |
completed | April 19, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69e3cde815e08190881972e2d80d151e |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:09 a.m.