Triple
T21665834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Visco |
E534713
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Ignazio Visco |
—
|
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: Ignazio Visco | Statement: [Visco, hasNotableBearer, Ignazio Visco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ignazio Visco Context triple: [Visco, hasNotableBearer, Ignazio Visco]
-
A.
Ignazio Visco
chosen
Ignazio Visco is an Italian economist who served as Governor of the Bank of Italy.
-
B.
Gerardo Amato
Gerardo Amato is an Italian actor known for his work in film, television, and theater.
-
C.
Mario Draghi
Mario Draghi is an Italian economist and former President of the European Central Bank who played a key role in managing the eurozone debt crisis.
-
D.
Roberto Formigoni
Roberto Formigoni is an Italian politician best known for his long tenure as President of the Lombardy region and his prominent role in center-right national politics.
-
E.
Francesco Buti
Francesco Buti was a 17th-century Italian poet and librettist active in the French court, known for writing opera texts for composers such as Francesco Cavalli.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c0b26c8819092c13e59dcc3c25c |
completed | April 27, 2026, 2 p.m. |
Created at: April 16, 2026, 6:36 p.m.