Triple
T24622733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apostolic Vicar of Dakar |
E609455
|
entity |
| Predicate | isPredecessorOfficeOf |
P72167
|
FINISHED |
| Object | Bishop of Dakar |
—
|
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: Bishop of Dakar | Statement: [Apostolic Vicar of Dakar, isPredecessorOfficeOf, Bishop of Dakar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPredecessorOfficeOf Context triple: [Apostolic Vicar of Dakar, isPredecessorOfficeOf, Bishop of Dakar]
-
A.
predecessorInOffice
Indicates that one officeholder directly held a particular position before another officeholder in an official succession.
-
B.
previousOffice
chosen
Indicates that one office or position was held immediately before another in a sequence of offices.
-
C.
precededByOfficeHolder
Indicates that one office holder directly held a position before another office holder in a sequence of occupants of the same office.
-
D.
predecessorInRole
Indicates that one entity previously held a particular role or position that was later occupied by another entity.
-
E.
successorOfficeTo
Indicates that one office or position directly follows and replaces another in an official sequence or hierarchy.
- 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_69e2c4d1d3708190a0f2dc6a3a8523bb |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6d0ab708190b2e3b94dd20ca76b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:32 a.m.