Triple
T7527237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Ranieri |
E177923
|
entity |
| Predicate | hasTypeOfSainthood |
P18301
|
FINISHED |
| Object | confessor |
—
|
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: confessor | Statement: [Saint Ranieri, hasTypeOfSainthood, confessor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfSainthood Context triple: [Saint Ranieri, hasTypeOfSainthood, confessor]
-
A.
typeOfSaint
chosen
Indicates that one entity is classified as a specific kind or category of saint in relation to another entity.
-
B.
hasPatronSaint
Indicates that one entity serves as the patron saint associated with, protecting, or representing another entity.
-
C.
dateOfCanonizationStatus
Indicates the date on which an entity’s canonization status (such as being declared a saint or blessed) was formally conferred or recorded.
-
D.
inCanonizationStatus
Indicates that an entity has a specific status or stage within a formal canonization process.
-
E.
hasClergyType
Indicates the specific category or role of clergy associated with an 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_69c69f29bf3081909a146aec7755f185 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f81cc5748190818443c48c9e3114 |
completed | March 27, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d6bb808190bdd04499fd3bceb6 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:47 p.m.