Triple
T9140277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Mary of the See |
E219307
|
entity |
| Predicate | hasPatronageScope |
P75457
|
FINISHED |
| Object | cathedral |
—
|
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: cathedral | Statement: [Saint Mary of the See, hasPatronageScope, cathedral]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPatronageScope Context triple: [Saint Mary of the See, hasPatronageScope, cathedral]
-
A.
hasPatronageOver
Indicates that one entity serves as a patron, sponsor, or protector for another, exercising support, guidance, or authority over it.
-
B.
hasInfluenceScope
chosen
Indicates the range or extent within which an entity’s influence, impact, or authority is effective or applicable.
-
C.
hasNotablePatron
Indicates that an entity is significantly supported, sponsored, or championed by a distinguished or influential patron.
-
D.
hasRecognitionScope
Indicates the extent or context within which a recognition, award, or acknowledgment is valid or applies.
-
E.
typeOfPatronage
Indicates the specific kind or category of support, sponsorship, or backing that one entity provides to 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_69ca83e012288190a5771058adbaabd2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8f2537881908956a9b0516e2d49 |
completed | April 1, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69cc6603ce8c8190bf6e8d6754bdec54 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:19 p.m.