Triple
T22940329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leslie Greif |
E569707
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Last Don |
—
|
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: The Last Don | Statement: [Leslie Greif, notableWork, The Last Don]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Last Don Context triple: [Leslie Greif, notableWork, The Last Don]
-
A.
The Last Don
chosen
The Last Don is a crime novel by Mario Puzo that follows the inner workings, power struggles, and eventual decline of a powerful American Mafia family.
-
B.
The Last Don
The Last Don is the debut studio album by Puerto Rican reggaeton artist Don Omar, widely credited with helping popularize reggaeton internationally in the early 2000s.
-
C.
The Mob
The Mob is an American hard rock band best known for featuring virtuoso guitarist Reb Beach and blending melodic rock with powerful vocals and guitar-driven sound.
-
D.
The Mob
The Mob is a 1951 American film noir crime drama starring Broderick Crawford as a tough undercover cop infiltrating a corrupt waterfront underworld.
-
E.
Mafioso
Mafioso is a hip-hop project by Chicago rapper Brian Fresco that showcases his gritty lyricism and street-influenced storytelling.
- 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_69e24590862c8190858f180ad302adab |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1813844b88190b05d3829b0c423c4 |
completed | April 29, 2026, 3:55 a.m. |
Created at: April 17, 2026, 3:45 p.m.