Triple
T8441871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Hill |
E199367
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Red Heat |
E308003
|
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: Red Heat | Statement: [Walter Hill, notableWork, Red Heat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Red Heat Context triple: [Walter Hill, notableWork, Red Heat]
-
A.
Red Heat
chosen
Red Heat is a 1988 buddy-cop action film starring Arnold Schwarzenegger and James Belushi, directed by Walter Hill.
-
B.
Hard Target
Hard Target is a 1993 American action film directed by John Woo and starring Jean-Claude Van Damme, known for its stylized violence and Woo’s Hollywood debut.
-
C.
Homicide Squad
The Homicide Squad is a specialized New York City Police Department unit dedicated to investigating and solving murder cases.
-
D.
Killer Force
Killer Force is a 1976 action-thriller film about a security chief investigating a suspected diamond heist at a South African mine.
-
E.
Righteous Kill
Righteous Kill is a 2008 crime thriller film best known for pairing Robert De Niro and Al Pacino as veteran New York City detectives hunting a possible serial killer.
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1da3a99481909c9beae665bb5b83 |
completed | April 2, 2026, 7:41 a.m. |
Created at: March 30, 2026, 6:08 p.m.