Triple
T3108392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince-Bishopric of Minden |
E64889
|
entity |
| Predicate | hadOfficeHolderType |
P16376
|
FINISHED |
| Object | prince-bishop |
—
|
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-bishop | Statement: [Prince-Bishopric of Minden, hadOfficeHolderType, prince-bishop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadOfficeHolderType Context triple: [Prince-Bishopric of Minden, hadOfficeHolderType, prince-bishop]
-
A.
hasOfficeHolderType
chosen
Indicates that an office or position is associated with a specific type or category of office holder (e.g., elected official, appointed official).
-
B.
hasHeldOfficeType
Indicates that an entity has at some time occupied or served in a specified type or category of office or position.
-
C.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
-
D.
officeHolderMayBe
Indicates that a specified person is permitted or eligible to hold a particular office or position.
-
E.
involvesOfficeHolder
Indicates that the relationship or action includes or pertains to a person currently holding a specific office or official position.
- 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada29eacc88190a19c5ca8e53e3dca |
completed | March 8, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69ad9df25d4c81908ff0f6cff55d0563 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:04 p.m.