Triple
T37969314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | cathedral chapter of Regensburg |
E947234
|
entity |
| Predicate | typeOfClerics |
P3092
|
FINISHED |
| Object | secular canons |
—
|
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: secular canons | Statement: [cathedral chapter of Regensburg, typeOfClerics, secular canons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfClerics Context triple: [cathedral chapter of Regensburg, typeOfClerics, secular canons]
-
A.
isCleric
Indicates that an entity holds the role or status of a cleric, typically serving a religious or spiritual function.
-
B.
hasClergyType
chosen
Indicates the specific category or role of clergy associated with an entity.
-
C.
hasClericalProtagonist
Indicates that the main character in the work is a member of the clergy or holds a religious office.
-
D.
typeOfSaint
Indicates that one entity is classified as a specific kind or category of saint in relation to another entity.
-
E.
priests
Indicates that the subject serves in a religious or spiritual officiating role, typically performing sacred rituals or duties for a faith community.
- 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_69f76ef7db908190bba6086673a32300 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:20 p.m.