Triple
T12425524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rambo film series |
E296888
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Avi Lerner |
E303929
|
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: Avi Lerner | Statement: [Rambo film series, producer, Avi Lerner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avi Lerner Context triple: [Rambo film series, producer, Avi Lerner]
-
A.
Avi Lerner
chosen
Avi Lerner is an Israeli-American film producer and founder of Millennium Films, known for financing and producing numerous action movies and franchises.
-
B.
Avi Rothman
Avi Rothman is an American actor, writer, and comedian known for his work in film and television and for being married to actress and comedian Kristen Wiig.
-
C.
Avi Goldstein
Avi Goldstein is an individual notable enough to be recognized as a prominent bearer of the surname Goldstein.
-
D.
Avi Belleli
Avi Belleli is an Israeli composer and musician best known for his atmospheric scores for film and television, including the acclaimed series "Prisoners of War."
-
E.
Yariv Lerner
Yariv Lerner is a film producer best known for his work on action movies, including serving as a producer on "Rambo: Last Blood."
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d7b6bd08190b30beba393a5b1e7 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64b97df9081909b281ed6c568fa37 |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:55 p.m.