Triple
T15345822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenland (film) |
E366913
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Alan Siegel |
E430149
|
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: Alan Siegel | Statement: [Greenland (film), producer, Alan Siegel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alan Siegel Context triple: [Greenland (film), producer, Alan Siegel]
-
A.
Alan Siegel
chosen
Alan Siegel is a film producer best known for his long-running collaboration with actor Gerard Butler on action and thriller movies.
-
B.
Ian Siegel
Ian Siegel is an American entrepreneur best known as the co-founder and longtime CEO of the online employment marketplace ZipRecruiter.
-
C.
Lou Scheimer
Lou Scheimer was an American animator, producer, and co-founder of the studio behind many classic Saturday-morning cartoons, including "He-Man and the Masters of the Universe" and "Fat Albert and the Cosby Kids."
-
D.
J. David Siegel
J. David Siegel is a film editor known for his work on major animated features, including the superhero comedy "DC League of Super-Pets."
-
E.
Eric Siegel
Eric Siegel is an American actor and television writer best known for his work on series such as "The Goldbergs."
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e1749bc8190a8b9cbcb27288a5b |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56b4c6c881908ac7887a88f80829 |
completed | May 9, 2026, 3:45 p.m. |
Created at: April 10, 2026, 3:17 a.m.