Triple
T574403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shikoku |
E13729
|
entity |
| Predicate | pilgrimageTempleCount |
P16195
|
FINISHED |
| Object | 88 |
—
|
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: 88 | Statement: [Shikoku, pilgrimageTempleCount, 88]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pilgrimageTempleCount Context triple: [Shikoku, pilgrimageTempleCount, 88]
-
A.
associatedTemple
Indicates a relationship where one entity is linked or connected to a particular temple, typically as its relevant or related religious site.
-
B.
enshrines
Indicates that one entity formally preserves, protects, or honors another by giving it a permanent, often sacred or legally recognized, status.
-
C.
mainTemple
Indicates that one entity serves as the primary or central temple associated with another entity.
-
D.
associatedWithTempleTown
Indicates a relationship where an entity has a connection or linkage to a town that is characterized by or centered around a temple.
-
E.
lastMajorTempleClosed
Indicates the time or event at which the final significant temple associated with an entity was permanently closed.
- F. None of above. chosen
Provenance (4 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b4c23548190a3b883239c7c78c8 |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c4969c819080375d08f9eec50c |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a498dd579081908e02368a4c5efc8c |
completed | March 1, 2026, 7:51 p.m. |
Created at: March 1, 2026, 7:33 p.m.