Triple
T10530106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew G. Vajna |
E248416
|
entity |
| Predicate | name |
P16
|
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: [Andrew G. Vajna, name, Andrew G. Vajna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew G. Vajna Context triple: [Andrew G. Vajna, name, 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.
Stephen D. Mastrofski
Stephen D. Mastrofski is an American criminologist known for his influential research on policing practices and critical evaluations of theories such as broken windows policing.
-
C.
Andrew J. Novobilski
Andrew J. Novobilski is a computer scientist and author known for co-writing influential work on the Objective-C programming language alongside Brad Cox.
-
D.
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.
-
E.
Michael A. Helfant
Michael A. Helfant is a film producer and entertainment executive known for his work on genre and thriller projects, including the 2013 crime thriller "The Call."
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509f7d8ac8190b90c1a7f77b23545 |
completed | April 7, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef8185c6e08190949020a80c24f2b8 |
completed | April 27, 2026, 3:32 p.m. |
Created at: April 6, 2026, 12:30 p.m.