Triple
T35884915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schoenstatt Shrine |
E1037614
|
entity |
| Predicate | hasReplicaShrinesIn |
P27587
|
FINISHED |
| Object | many countries worldwide |
—
|
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: many countries worldwide | Statement: [Schoenstatt Shrine, hasReplicaShrinesIn, many countries worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReplicaShrinesIn Context triple: [Schoenstatt Shrine, hasReplicaShrinesIn, many countries worldwide]
-
A.
hasShrinesIn
chosen
Indicates that one entity possesses or maintains shrines that are located within the area or domain of another entity.
-
B.
hasShrines
Indicates that one entity contains, hosts, or is associated with one or more shrines dedicated to another entity.
-
C.
containsShrine
Indicates that one entity includes or has within its boundaries a shrine associated with it.
-
D.
hasInnerShrine
Indicates that one entity contains or includes another entity that functions as an inner shrine within it.
-
E.
hasNearbyShrine
Indicates that one entity is located close to or in the vicinity of a shrine associated with another entity.
- 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_69f76e1f4d748190bb55594d8441d70e |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.