Triple
T33528107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Confessional of the Black Penitents |
E858696
|
entity |
| Predicate | relatedToSetting |
P44691
|
FINISHED |
| Object | Italian Catholic institutions |
—
|
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: Italian Catholic institutions | Statement: [The Confessional of the Black Penitents, relatedToSetting, Italian Catholic institutions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToSetting Context triple: [The Confessional of the Black Penitents, relatedToSetting, Italian Catholic institutions]
-
A.
associatedWithSetting
chosen
Indicates that one entity is connected or linked to a particular context, environment, or setting in which it occurs or is relevant.
-
B.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
C.
relatedToFeature
Indicates that there is a general association or connection between an entity and a particular feature.
-
D.
relatedToProduct
Indicates a general association or connection between an entity and a specific product, without specifying the exact nature of that relationship.
-
E.
relatedToTerm
Indicates a general, non-specific relationship or association between one term and another.
- 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_69f349781c6c819082c516b260efe7e2 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:39 a.m.