Triple
T1755128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theatinerkirche, Munich |
E38532
|
entity |
| Predicate | currentParishUse |
P25209
|
FINISHED |
| Object | Roman Catholic parish church |
—
|
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: Roman Catholic parish church | Statement: [Theatinerkirche, Munich, currentParishUse, Roman Catholic parish church]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentParishUse Context triple: [Theatinerkirche, Munich, currentParishUse, Roman Catholic parish church]
-
A.
parish
Indicates that an entity is administratively or ecclesiastically associated with a particular parish.
-
B.
hasDenominationalUse
chosen
Indicates that something is used or applied within the context of a particular religious denomination or sect.
-
C.
hasParishType
Indicates that an entity is associated with or classified by a specific type or category of parish.
-
D.
hasChurch
Indicates that a place or entity possesses, contains, or is associated with a church.
-
E.
numberOfParishes
Indicates the total count of parishes associated with a given 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_69a8862bdb2081908aefe831c8aa8017 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba6a63f588190b53b39c6b97d74f4 |
completed | March 7, 2026, 4:16 a.m. |
| PD | Predicate disambiguation | batch_69aa61c7ef4c8190abec87c96a787d82 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.