Triple
T27553345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince-bishop of Neuss |
E695564
|
entity |
| Predicate | hasSecularRole |
P102197
|
FINISHED |
| Object | prince |
—
|
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: prince | Statement: [Prince-bishop of Neuss, hasSecularRole, prince]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecularRole Context triple: [Prince-bishop of Neuss, hasSecularRole, prince]
-
A.
hasSecularStatus
Indicates that an entity holds a non-religious, secular standing or classification within a given context.
-
B.
hasSecularRank
chosen
Indicates that one entity holds a specific position or level within a non-religious (secular) hierarchy relative to another entity.
-
C.
hasSecularAspects
Indicates that something includes or exhibits non-religious, worldly, or secular characteristics or dimensions.
-
D.
hasReligiousRoleEquivalent
Indicates that two religious roles are considered functionally or hierarchically equivalent within or across religious traditions.
-
E.
hasSecularUse
Indicates that something is used in a non-religious, worldly, or secular context or purpose.
- 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_69ef5387e97c8190a9dab040d21cd048 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69fce7671f108190bf3ebf54339068b5 |
completed | May 7, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69fce5b5a84c81908ac1b5b9f08d48d0 |
completed | May 7, 2026, 7:19 p.m. |
Created at: April 27, 2026, 1:35 p.m.