Triple
T8085672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYPD Red series |
E188724
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | crime thriller series |
C6645
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: crime thriller series Context triple: [NYPD Red series, instanceOf, crime thriller series]
-
A.
detective fiction series
chosen
A detective fiction series is a collection of interconnected stories or novels that follow one or more investigators as they solve mysteries or crimes, often featuring recurring characters, settings, and thematic elements.
-
B.
crime thriller play
A crime thriller play is a stage drama that centers on suspenseful investigations, criminal schemes, and high-stakes confrontations, keeping the audience in tension as mysteries unfold in real time.
-
C.
legal thriller film
A legal thriller film is a suspense-driven movie that centers on courtroom drama, legal conflicts, and investigations, often involving high-stakes cases, moral ambiguity, and twists surrounding the pursuit of justice.
-
D.
medical thriller film
A medical thriller film is a suspense-driven movie that centers on high-stakes medical settings, procedures, or experiments, often involving ethical dilemmas, deadly outbreaks, or sinister conspiracies within the healthcare or scientific world.
-
E.
psychological crime thriller film
A psychological crime thriller film is a suspense-driven movie that focuses on the mental and emotional states of characters involved in criminal activities, often blurring the line between reality and perception while unraveling complex mysteries.
- F. None of above.
Provenance (1 batch)
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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
Created at: March 30, 2026, 5:29 p.m.