Triple
T17017986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The International |
E412870
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Charles Roven |
E11616
|
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: Charles Roven | Statement: [The International, producer, Charles Roven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charles Roven Context triple: [The International, producer, Charles Roven]
-
A.
Charles Roven
chosen
Charles Roven is an American film producer known for his work on major Hollywood blockbusters, including Christopher Nolan’s films such as Oppenheimer and The Dark Knight trilogy.
-
B.
Michael Seitzman
Michael Seitzman is an American screenwriter and producer known for his work on films such as "North Country" and for creating and producing several television series.
-
C.
Robert Vogel
Robert Vogel is a world-renowned practical shooting champion and firearms instructor known for his multiple IPSC and USPSA titles.
-
D.
Joel Silver
Joel Silver is a prominent American film producer known for high-octane action and genre-defining hits such as the "Lethal Weapon" and "The Matrix" franchises.
-
E.
John Seitz
John Seitz was an American cinematographer renowned for his influential work in classic Hollywood cinema, particularly in film noir and science fiction.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d480a58c8190a3912d26debb4311 |
completed | April 18, 2026, 6:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b4d6cb881909b64b4368fd97fa9 |
completed | May 10, 2026, 11:57 p.m. |
Created at: April 10, 2026, 5:33 a.m.