Triple
T9432592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorenza Izzo |
E227418
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Izzo |
E577050
|
NE 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: Izzo | Statement: [Lorenza Izzo, familyName, Izzo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Izzo Context triple: [Lorenza Izzo, familyName, Izzo]
-
A.
Izzo
chosen
Izzo is the surname of Tom Izzo, the longtime and highly successful head coach of the Michigan State University men's basketball team.
-
B.
Altobelli
Altobelli is an Italian surname most notably associated with figures in professional baseball and football, including former MLB manager Joe Altobelli.
-
C.
Riggo
Riggo is the nickname of John Riggins, a Hall of Fame NFL running back best known for his powerful rushing style with the Washington Redskins.
-
D.
Zito
Zito is a surname most notably associated with Barry Zito, a former Major League Baseball pitcher and Cy Young Award winner.
-
E.
Dario
Dario is a masculine given name of Italian origin, commonly used in various European and Latin American countries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7e61a114819081fc4a2ad39c96ba |
completed | April 1, 2026, 8:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1104033c08190a3670b017bd984d5 |
completed | April 4, 2026, 1:21 p.m. |
Created at: March 30, 2026, 7:49 p.m.