Triple
T15308269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Bossuet |
E365959
|
entity |
| Predicate | depictsReligiousRole |
P51786
|
FINISHED |
| Object | Catholic 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: Catholic bishop | Statement: [Portrait of Bossuet, depictsReligiousRole, Catholic bishop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsReligiousRole Context triple: [Portrait of Bossuet, depictsReligiousRole, Catholic bishop]
-
A.
religiousTextRole
Indicates the specific role or function that a religious text has in relation to a person, group, practice, or tradition.
-
B.
eraOfReligiousFunction
Indicates the historical time period during which a religious role, office, or function was actively performed or held.
-
C.
depictedDeity
Indicates that one entity is a deity who is shown or represented in an image, artwork, or visual depiction associated with another entity.
-
D.
regionReligiousRole
Indicates the role or function that religion plays within a particular region, such as its religious status, significance, or designated religious purpose.
-
E.
associatedReligionRole
chosen
Indicates that one entity holds a specific religious role, office, or function in relation to another entity.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03cd001b48190bbdd69337efdb907 |
completed | April 16, 2026, 1:35 a.m. |
| PD | Predicate disambiguation | batch_69deca935e2c8190b640987ddfc542b9 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:16 a.m.