Triple

T14851384
Position Surface form Disambiguated ID Type / Status
Subject Police E349234 entity
Predicate hasSpecializedUnit P1198 FINISHED
Object Cybercrime unit E656619 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: Cybercrime unit | Statement: [Police, hasSpecializedUnit, Cybercrime unit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cybercrime unit
Context triple: [Police, hasSpecializedUnit, Cybercrime unit]
  • A. Cybercrime unit chosen
    The Cybercrime unit is a specialized law enforcement team focused on investigating and combating offenses committed using computers, networks, and digital technologies.
  • B. Cyber Crime Unit
    The Cyber Crime Unit is a specialist division of the City of London Police dedicated to investigating and combating cyber-enabled and computer-based criminal activity.
  • C. Cyber Crime Unit
    The Cyber Crime Unit is a specialized division of the Detroit Police Department focused on investigating and combating computer-based and digital crimes.
  • D. Cyber Crime Unit
    The Cyber Crime Unit is a specialized division of York Regional Police that investigates and combats offenses involving computers, networks, and digital evidence.
  • E. Cyber Crime Unit
    The Cyber Crime Unit is a specialized division of the Uttar Pradesh Police responsible for investigating and combating offenses involving computers, networks, and digital technologies.
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded441e70881909bbf62b66d932aff completed April 14, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe6504ac6081908074231cf628fd39 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:54 a.m.