Triple
T22673429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Good Guy |
E560281
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Julio DePietro |
—
|
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: Julio DePietro | Statement: [The Good Guy, writer, Julio DePietro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julio DePietro Context triple: [The Good Guy, writer, Julio DePietro]
-
A.
Julio DePietro
chosen
Julio DePietro is an American filmmaker and screenwriter best known for his work in independent cinema.
-
B.
Ernesto Botto
Ernesto Botto was an Italian World War II fighter ace and senior aviator who became a leading figure in the air force of the Italian Social Republic after the 1943 armistice.
-
C.
Hector Colantoni
Hector Colantoni is known primarily as the brother of Canadian actor Enrico Colantoni.
-
D.
Francisco Tamburini
Francisco Tamburini was an Italian-Argentine architect renowned for designing some of Buenos Aires’ most iconic late 19th-century public buildings.
-
E.
Armando Barillo
Armando Barillo is a powerful Mexican drug lord and primary antagonist in the action film "Once Upon a Time in Mexico."
- 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17821daf88190b18a73a222fc22fb |
completed | April 29, 2026, 3:16 a.m. |
Created at: April 17, 2026, 3:10 p.m.