Triple

T13114135
Position Surface form Disambiguated ID Type / Status
Subject Vorpommern-Greifswald E311048 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object VG E768100 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: VG | Statement: [Vorpommern-Greifswald, vehicleRegistrationCode, VG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VG
Context triple: [Vorpommern-Greifswald, vehicleRegistrationCode, VG]
  • A. VG
    VG is the two-letter ISO 3166 country code assigned to the British Virgin Islands.
  • B. VG chosen
    VG is the vehicle registration code used on license plates for the district of Vorpommern-Greifswald in the German state of Mecklenburg-Vorpommern.
  • C. VG
    VG is a major Norwegian newspaper and online news outlet known for its wide national readership and influential coverage of current affairs.
  • D. VT
    VT is the commonly used abbreviation for Virginia Tech, a major public research university in Blacksburg, Virginia.
  • E. VT
    VT is the vehicle registration code used on license plates for vehicles registered in the Province of Viterbo in Italy.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817f8ee8819084078b4bec5e4f18 completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e28105c481908781775ba489c296 completed May 3, 2026, 5:52 a.m.
Created at: April 9, 2026, 9:06 p.m.