Triple
T21736205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medicine Man |
E536530
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | John McTiernan |
—
|
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: John McTiernan | Statement: [Medicine Man, director, John McTiernan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John McTiernan Context triple: [Medicine Man, director, John McTiernan]
-
A.
John McTiernan
chosen
John McTiernan is an American film director best known for influential action movies such as "Die Hard" and "Predator."
-
B.
David Friedkin
David Friedkin was an American screenwriter, director, and producer known for his work in mid-20th-century film and television.
-
C.
John Boyd-Carpenter
John Boyd-Carpenter was a British Conservative politician and government minister who held several senior posts in the mid-20th century, including key roles in economic and social policy.
-
D.
Peter Hyams
Peter Hyams is an American filmmaker known for directing and often writing and shooting genre films such as science fiction thrillers and action movies.
-
E.
Christopher Landon
Christopher Landon is an American film director, screenwriter, and producer best known for his work on the "Paranormal Activity" series and the "Happy Death Day" films.
- 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.