Triple
T5143084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario F. Kassar |
E116004
|
entity |
| Predicate | notablePartner |
P14988
|
FINISHED |
| Object | Andrew G. Vajna |
E248416
|
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: Andrew G. Vajna | Statement: [Mario F. Kassar, notablePartner, Andrew G. Vajna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew G. Vajna Context triple: [Mario F. Kassar, notablePartner, Andrew G. Vajna]
-
A.
Andrew G. Vajna
chosen
Andrew G. Vajna was a Hungarian-American film producer best known for backing major action franchises such as the Rambo and Terminator series.
-
B.
Robert M. Weitman
Robert M. Weitman was an American film producer active in mid-20th-century Hollywood, known for overseeing a range of studio features and genre films.
-
C.
Stephen J. Rivele
Stephen J. Rivele is an American screenwriter best known for co-writing acclaimed biographical and historical films such as "Nixon" and "Ali."
-
D.
Michael P. Brenner
Michael P. Brenner is an American applied mathematician and physicist known for his influential work in fluid dynamics and complex systems.
-
E.
Richard C. Kratina
Richard C. Kratina was a cinematographer best known for his work on the 1977 horror film "The Sentinel."
- 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_69bd4446c0e08190a7c29dc74976bf03 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7883004881909c763da818d9b6e2 |
completed | March 20, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfc018410c8190bfd0138ced6c2151 |
completed | March 22, 2026, 10:10 a.m. |
Created at: March 20, 2026, 1:43 p.m.