Triple
T11865730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Peter and Paul Church, Eisleben |
E282276
|
entity |
| Predicate | hasBaptismalFont |
P101958
|
FINISHED |
| Object | baptismal font associated with Martin Luther |
—
|
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: baptismal font associated with Martin Luther | Statement: [St. Peter and Paul Church, Eisleben, hasBaptismalFont, baptismal font associated with Martin Luther]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBaptismalFont Context triple: [St. Peter and Paul Church, Eisleben, hasBaptismalFont, baptismal font associated with Martin Luther]
-
A.
baptismalFontUsedFor
Indicates that a particular baptismal font is used to perform or conduct a specific baptism or set of baptisms.
-
B.
baptized
Indicates that one entity performed or underwent the religious rite of baptism in relation to another entity or context.
-
C.
baptismName
Indicates the name an individual receives or uses specifically in the context of a baptism ceremony.
-
D.
baptismYear
Indicates the calendar year in which an entity’s baptism took place.
-
E.
christenedBy
Indicates that an entity received its name or was formally dedicated through a christening performed by another entity.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a73a233081909449ab294d01a512 |
completed | April 10, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69d8a2589f0c8190ad82ff11acabae93 |
completed | April 10, 2026, 7:10 a.m. |
| PDg | Predicate description generation | batch_69d8a43cc0c881909fed7cd759fe90b1 |
completed | April 10, 2026, 7:18 a.m. |
Created at: April 8, 2026, 9:43 p.m.