Triple
T34464182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cardinal-Deacon of Sant’Apollinare alle Terme Neroniane-Alessandrine |
E884724
|
entity |
| Predicate | typeOfCardinalTitle |
P101310
|
FINISHED |
| Object | diaconia |
—
|
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: diaconia | Statement: [Cardinal-Deacon of Sant’Apollinare alle Terme Neroniane-Alessandrine, typeOfCardinalTitle, diaconia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCardinalTitle Context triple: [Cardinal-Deacon of Sant’Apollinare alle Terme Neroniane-Alessandrine, typeOfCardinalTitle, diaconia]
-
A.
typeOfCardinal
Indicates a classification relationship where one entity is a specific kind or subtype of a broader cardinal category represented by the other entity.
-
B.
hasCardinalTitle
Indicates that an entity holds or is associated with the formal title or rank of a cardinal.
-
C.
cardinalateTitle
chosen
Indicates the specific cardinal rank or title conferred on a person within the College of Cardinals.
-
D.
cardinalName
Indicates that an entity has a specific cardinal (numerical order) name or label.
-
E.
createdCardinalOf
Indicates that an entity established or founded the position or office of a cardinal for 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_69f349c73a94819094dfcf50d00620b8 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a013c50bcb8819086d163f1a796a9b8 |
completed | May 11, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_6a013c01bac88190b15c70910c02a8a7 |
completed | May 11, 2026, 2:16 a.m. |
Created at: May 1, 2026, 2 a.m.