Triple

T21456748
Position Surface form Disambiguated ID Type / Status
Subject Dranske E529360 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object VR 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: VR | Statement: [Dranske, vehicleRegistrationCode, VR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VR
Context triple: [Dranske, vehicleRegistrationCode, VR]
  • A. VR chosen
    VR is a vehicle registration code used on license plates to identify vehicles registered in Bergen auf Rügen, Germany.
  • B. VR
    VR is the abbreviation used for the Volunteer Reserves, the part-time volunteer component of the British Armed Forces.
  • C. VR
    VR is the provincial code for the Province of Verona in the Veneto region of northern Italy.
  • D. VR
    VR is a Finnish state-owned railway company that operates most of Finland’s passenger and freight rail services.
  • E. VRT
    VRT is Belgium’s public-service broadcaster for the Flemish Community, providing television, radio, and online media.
  • 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_69e0c458133481908ae8b41a12c4edec completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9e9d7af248190a3bc06a390f390bf completed April 23, 2026, 9:43 a.m.
Created at: April 16, 2026, 6:08 p.m.