Triple
T3119979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan of Saint Petersburg and Ladoga |
E65158
|
entity |
| Predicate | hasTitleHolderType |
P22451
|
FINISHED |
| Object | male 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: male bishop | Statement: [Metropolitan of Saint Petersburg and Ladoga, hasTitleHolderType, male bishop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleHolderType Context triple: [Metropolitan of Saint Petersburg and Ladoga, hasTitleHolderType, male bishop]
-
A.
hasTitleHolder
Indicates that one entity is the current or designated holder of a specific title, position, or honor associated with another entity.
-
B.
hasTitleType
Indicates that an entity holds a specific kind or category of title (such as job title, honorific, or formal designation).
-
C.
refersToTitleHolder
Indicates that one entity makes reference to, or designates, the entity that currently holds a specific title or position.
-
D.
titleHolderType
chosen
Indicates the specific role or capacity in which an entity holds a title (e.g., owner, trustee, beneficiary).
-
E.
hasPositionHolderType
Indicates that an entity’s role or office is associated with a specific type or category of position holder.
- 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_69ad857fcc088190b0c4d45a5cde6f61 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada4eb6a6081909df41f67999eb4ff |
completed | March 8, 2026, 4:33 p.m. |
| PD | Predicate disambiguation | batch_69ad9df455088190940ad04419772dc8 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:04 p.m.