Triple
T14340780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kumadaniji |
E355593
|
entity |
| Predicate | templeNumberInShikokuPilgrimage |
P16195
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Kumadaniji, templeNumberInShikokuPilgrimage, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: templeNumberInShikokuPilgrimage Context triple: [Kumadaniji, templeNumberInShikokuPilgrimage, 8]
-
A.
pilgrimageTempleCount
chosen
Indicates the number of temples associated with or visited during a particular pilgrimage.
-
B.
numberOfShrines
Indicates the total count of shrines associated with a given entity or context.
-
C.
associatedTemple
Indicates a relationship where one entity is linked or connected to a particular temple, typically as its relevant or related religious site.
-
D.
countryShrineOf
Indicates that a country is the location or host nation of a particular shrine.
-
E.
enshrines
Indicates that one entity formally preserves, protects, or honors another by giving it a permanent, often sacred or legally recognized, status.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8e87febc8190a63c668cbd0fd713 |
completed | April 14, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69de2a9958e881909d03ac03f135163e |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:14 a.m.