Triple
T21736206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medicine Man |
E536530
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Andrew G. Vajna |
—
|
NE NERFINISHED |
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: [Medicine Man, producer, Andrew G. Vajna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew G. Vajna Context triple: [Medicine Man, producer, 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.
Andrew P. Wypych
Andrew P. Wypych is a Polish-born Roman Catholic prelate who serves as an auxiliary bishop in the Archdiocese of Chicago.
-
C.
Ronald N. Yurcak
Ronald N. Yurcak is an individual honored as the namesake of Yurcak Field, a sports venue associated with Rutgers University.
-
D.
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.
-
E.
Garth H. Drabinsky
Garth H. Drabinsky is a Canadian theatrical producer and former film executive known for his high-profile stage productions and controversial legal troubles.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46df5448190b4322127ffc4c690 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69effd0c0a088190bd1926fa4b73d8f4 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 16, 2026, 6:49 p.m.