Triple
T20910330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Massimo Ferrero |
E514922
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Massimo Ferrero |
—
|
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: Massimo Ferrero | Statement: [Massimo Ferrero, name, Massimo Ferrero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Massimo Ferrero Context triple: [Massimo Ferrero, name, Massimo Ferrero]
-
A.
Massimo Ferrero
chosen
Massimo Ferrero is an Italian film producer and businessman best known for his controversial tenure as president and owner of Serie A football club Sampdoria.
-
B.
Stefano Rusconi
Stefano Rusconi is a former Italian professional basketball center who played in the NBA and was a prominent figure in European basketball during the late 1980s and 1990s.
-
C.
Massimo Bonetti
Massimo Bonetti is an Italian actor known for his work in film and television, particularly in Italian drama and crime productions.
-
D.
Aymo Maggi
Aymo Maggi was an Italian racing driver and aristocrat best known for co-founding the legendary Mille Miglia endurance road race.
-
E.
Andrea Bricco
Andrea Bricco is a food and lifestyle photographer known for her artful, atmospheric images featured in editorial and commercial work.
- 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6ec5d73c88190a48180a1eed88190 |
completed | April 21, 2026, 3:17 a.m. |
Created at: April 16, 2026, 12:48 p.m.