Triple
T3035468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Catholic Diocese of Nice |
E82997
|
entity |
| Predicate | hasBishopType |
P31297
|
FINISHED |
| Object | diocesan 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: diocesan bishop | Statement: [Roman Catholic Diocese of Nice, hasBishopType, diocesan bishop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBishopType Context triple: [Roman Catholic Diocese of Nice, hasBishopType, diocesan bishop]
-
A.
hasBishop
Indicates that one entity possesses, is assigned, or is associated with a bishop in relation to another entity.
-
B.
hasNumberOfBishops
Indicates the relationship that specifies how many bishops are associated with a given entity.
-
C.
typeOfBishop
chosen
Indicates that one entity is a specific kind or category of bishop in relation to another entity.
-
D.
hasPreviousBishop
Indicates that one bishop previously held the same episcopal position or office as another bishop.
-
E.
hasCastleType
Indicates that an entity is associated with, characterized by, or classified as a specific type of castle.
- 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_69ad8b2298908190a7cb4e9bdbf064d0 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9b2bb60c8190b1721f832f2581a1 |
completed | March 8, 2026, 3:52 p.m. |
| PD | Predicate disambiguation | batch_69ad961e2a408190afb1759132701305 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.