Triple
T8607546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fighting Marines |
E203838
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Nat Levine |
E503126
|
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: Nat Levine | Statement: [The Fighting Marines, producer, Nat Levine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nat Levine Context triple: [The Fighting Marines, producer, Nat Levine]
-
A.
Nat Levine
chosen
Nat Levine was an American film producer best known for founding Mascot Pictures and producing popular movie serials during the 1920s and 1930s.
-
B.
Sam Levine
Sam Levine is an American animation director and storyboard artist known for co-directing the superhero comedy film "DC League of Super-Pets."
-
C.
Charles Michael Levine
Charles Michael Levine, better known as Chuck Lorre, is an American television writer, director, producer, and creator behind hit sitcoms such as "The Big Bang Theory," "Two and a Half Men," and "Dharma & Greg."
-
D.
Dan Levine
Dan Levine is a film producer best known for his work on the acclaimed science-fiction drama "Arrival."
-
E.
Mark Levine
Mark Levine is an American politician and public servant who serves as the borough president of Manhattan in New York City.
- 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_69ca832c23e4819095a9f3eea4a21828 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46ec301881908ce148a3f07069fe |
completed | March 31, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d065b11f3c81909c787d365b242d57 |
completed | April 4, 2026, 1:13 a.m. |
Created at: March 30, 2026, 6:25 p.m.