Triple
T37330957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Lady of Italy |
E926742
|
entity |
| Predicate | mayPatronize |
P187734
|
FINISHED |
| Object | cultural organizations |
—
|
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: cultural organizations | Statement: [First Lady of Italy, mayPatronize, cultural organizations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayPatronize Context triple: [First Lady of Italy, mayPatronize, cultural organizations]
-
A.
mayServe
Indicates that one entity is permitted or authorized to provide a service or function to another entity.
-
B.
mayRate
Indicates that one entity is permitted or authorized to assign a rating or evaluation to another entity.
-
C.
mayPromote
Indicates that one entity has the authority or permission to advance another entity to a higher rank, position, or status.
-
D.
coPatron
Indicates a relationship where two or more entities share joint responsibility or role as patrons supporting the same person, group, or endeavor.
-
E.
patroness
Indicates that a female person supports, sponsors, or acts as a benefactor for someone or something.
- F. None of above. chosen
Provenance (4 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_69f76eb386d88190a8d511aa11540dfc |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb78cbef988190b8f79d946b46e6b2 |
completed | May 6, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9ac5a08190b24ef308963fc52b |
completed | May 6, 2026, 3:13 p.m. |
| PDg | Predicate description generation | batch_69fb78c982ac8190846efe8f6209e5d1 |
completed | May 6, 2026, 5:22 p.m. |
Created at: May 3, 2026, 4:16 p.m.