Triple

T9780874
Position Surface form Disambiguated ID Type / Status
Subject Rob Huebel E237365 entity
Predicate hasActedIn P15620 FINISHED
Object Medical Police E820638 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: Medical Police | Statement: [Rob Huebel, hasActedIn, Medical Police]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Medical Police
Context triple: [Rob Huebel, hasActedIn, Medical Police]
  • A. Medical Police chosen
    Medical Police is a satirical comedy series that parodies medical dramas and crime procedurals, following two doctors who become government agents investigating a global pandemic.
  • B. Detective Service
    Detective Service is the investigative division of the South African Police Service responsible for conducting criminal investigations and solving serious crimes.
  • C. Police
    The police are a civil force empowered by the state to maintain public order, enforce laws, and prevent, detect, and investigate crime.
  • D. Police
    Police is a town in northwestern Poland, located in the West Pomeranian Voivodeship near Szczecin.
  • E. Crime Scene Unit
    The Crime Scene Unit is a specialized forensic division that processes and analyzes physical evidence from crime scenes to support criminal investigations.
  • 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_69ca84d975a08190aab25b02a89bdab3 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda1b0b15881909ef52d0156148c59 completed April 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c41b31b08190937f374c2d51aa1b completed April 5, 2026, 2:08 a.m.
Created at: March 30, 2026, 8:27 p.m.