Triple

T8238657
Position Surface form Disambiguated ID Type / Status
Subject Bad Kösen E192473 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object BLK E189699 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: BLK | Statement: [Bad Kösen, vehicleRegistrationCode, BLK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BLK
Context triple: [Bad Kösen, vehicleRegistrationCode, BLK]
  • A. BLK chosen
    BLK is the vehicle registration code used on license plates for the Burgenlandkreis district in the German state of Saxony-Anhalt.
  • B. Balck
    Balck is a German surname most notably associated with Hermann Balck, a prominent Wehrmacht general during World War II.
  • C. BLQ
    BLQ is the three-letter IATA airport code for Bologna Guglielmo Marconi Airport, serving the city of Bologna in northern Italy.
  • D. BLC
    BLC is the commonly used abbreviation for the Boston Landmarks Commission, the city agency responsible for identifying and protecting Boston’s historic buildings and districts.
  • E. Blacko
    Blacko is a small rural village in Lancashire, England, known for its scenic countryside and landmark Blacko Tower.
  • 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_69ca82dc8f148190a2c75a98501a7b91 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb783a8cf48190bf85394fd3bd79e2 completed March 31, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd3504e6ac8190b4cb12c80a7e7fc0 completed April 1, 2026, 3:08 p.m.
Created at: March 30, 2026, 5:47 p.m.