Triple
T18536165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Lady of Germany |
E452970
|
entity |
| Predicate | oftenPatronOf |
P68473
|
FINISHED |
| Object | charitable foundations |
—
|
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: charitable foundations | Statement: [First Lady of Germany, oftenPatronOf, charitable foundations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenPatronOf Context triple: [First Lady of Germany, oftenPatronOf, charitable foundations]
-
A.
usedAsPatronOf
chosen
Indicates that one entity serves as a patron or sponsor for another, providing support, endorsement, or backing.
-
B.
familyPatronOf
Indicates a relationship where one family acts as a patron, sponsor, or protector providing support or resources to another party.
-
C.
typeOfPatronage
Indicates the specific kind or category of support, sponsorship, or backing that one entity provides to another.
-
D.
cityPatron
Indicates that one entity serves as the patron, protector, or special guardian of a particular city.
-
E.
laterPatron
Indicates that one entity serves as a patron of another at a later time than some reference patronage relationship.
- 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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5340256d08190bf22d2cb064413b2 |
completed | April 19, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69e469e0025c81908f16ed4f922674af |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:37 a.m.