Triple
T4197973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Boys for Life |
E85998
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Dan Lebental |
E170921
|
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: Dan Lebental | Statement: [Bad Boys for Life, editedBy, Dan Lebental]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Lebental Context triple: [Bad Boys for Life, editedBy, Dan Lebental]
-
A.
Dan Lebental
chosen
Dan Lebental is an American film editor best known for his long-time collaboration with director Jon Favreau on major studio films such as the Iron Man series.
-
B.
Leon Feldhendler
Leon Feldhendler was a Polish Jewish resistance leader and Holocaust survivor best known for co-organizing the 1943 prisoner uprising at the Sobibor extermination camp.
-
C.
Dan Gershon
Dan Gershon is known as the brother of American actress Gina Gershon.
-
D.
Sam Levy
Sam Levy is an American cinematographer best known for his frequent collaborations with director Noah Baumbach and his work on acclaimed independent films.
-
E.
Leon Levy
Leon Levy was an American investor, philanthropist, and patron of the humanities known for his significant support of archaeology, the arts, and biographical scholarship.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0360bc8081908ceb2483eef89174 |
completed | March 9, 2026, 5:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf28ea49588190bf1bc4cb3ca4dcee |
completed | March 21, 2026, 11:25 p.m. |
Created at: March 9, 2026, 3:48 p.m.