Triple
T15347734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple 35: Kiyotakiji |
E366967
|
entity |
| Predicate | hasPilgrimageContext |
P73017
|
FINISHED |
| Object | Kūkai-related sacred places |
—
|
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: Kūkai-related sacred places | Statement: [Temple 35: Kiyotakiji, hasPilgrimageContext, Kūkai-related sacred places]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPilgrimageContext Context triple: [Temple 35: Kiyotakiji, hasPilgrimageContext, Kūkai-related sacred places]
-
A.
hasPilgrimageRegion
Indicates that an entity is associated with a specific region that serves as the destination or location for its pilgrimage activities.
-
B.
hasPilgrimageFrom
Indicates that a pilgrimage originates from or is undertaken starting at a specified location or source.
-
C.
hasPilgrimageFunctionSince
Indicates that an entity has served a pilgrimage-related role or function continuously since a specified point in time.
-
D.
hasPilgrimageActivity
chosen
Indicates that an entity engages in, organizes, or is associated with a religious pilgrimage activity.
-
E.
hasPilgrimageType
Indicates that an entity is associated with a specific type or category of pilgrimage.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e1749bc8190a8b9cbcb27288a5b |
completed | April 16, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69deca991e5081908b0df3d1ee7d5338 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:17 a.m.