Triple
T37023707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salesian Sisters (Daughters of Mary Help of Christians) |
E916289
|
entity |
| Predicate | hasSaintFounder |
P61877
|
FINISHED |
| Object | Saint John Bosco |
—
|
NE NERFINISHED |
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: Saint John Bosco | Statement: [Salesian Sisters (Daughters of Mary Help of Christians), hasSaintFounder, Saint John Bosco]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSaintFounder Context triple: [Salesian Sisters (Daughters of Mary Help of Christians), hasSaintFounder, Saint John Bosco]
-
A.
hasReligiousFounderAssociated
Indicates that an entity is associated with a specific religious founder, typically through origin, dedication, or foundational influence.
-
B.
hasPatronSaint
Indicates that one entity serves as the patron saint associated with, protecting, or representing another entity.
-
C.
founderOfCathedralStatus
Indicates that an entity holds the status or recognition of being the founder of a particular cathedral.
-
D.
founderOfOrder
Indicates that an entity established or created a particular order, organization, or structured group.
-
E.
founderReligiousOrder
chosen
Indicates that a person established or created a particular religious order.
- 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_69f76e920dc48190acb6bb7ebc4dffab |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:14 p.m.