Triple
T15720340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Training Day |
E381075
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Andrew Z. Davis |
E381075
|
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 Z. Davis | Statement: [Training Day, producer, Andrew Z. Davis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Z. Davis Context triple: [Training Day, producer, Andrew Z. Davis]
-
A.
Andrew Z. Davis
chosen
Andrew Z. Davis is a film producer best known for his work on the crime thriller "Training Day."
-
B.
Peter Davis
Peter Davis is a New Zealand academic and sociologist best known as the husband of former Prime Minister Helen Clark.
-
C.
Michael V. Drake
Michael V. Drake is an American academic leader and physician who has served as president of both The Ohio State University and the University of California system.
-
D.
Alexander J. Davis
Alexander J. Davis was a prominent 19th-century American architect known for his influential Gothic Revival and Greek Revival designs across the United States.
-
E.
Peter S. Davis
Peter S. Davis is a film producer best known for his work on genre films, including the Highlander franchise.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fb0b51081908e652ec4992296fa |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa9341a0c81909057dc338f218b85 |
completed | May 9, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:45 a.m.