Triple

T2136291
Position Surface form Disambiguated ID Type / Status
Subject Brandenburg E46660 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object B E78336 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: B | Statement: [Brandenburg, hasVehicleRegistrationCode, B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: B
Context triple: [Brandenburg, hasVehicleRegistrationCode, B]
  • A. B
    B is the designation of one of the main lines of the Paris RER commuter rail network, serving a major north–south axis through the Île-de-France region.
  • B. B chosen
    B is the vehicle registration code used on license plates for Berlin, Germany.
  • C. B
    B is an early systems programming language developed at Bell Labs that served as a direct precursor to the C programming language.
  • D. B
    B is a New York City Subway service that runs on the IND Sixth Avenue Line, providing local and express service through Manhattan and Brooklyn.
  • E. B3
    B3 is the third-generation Volkswagen Passat, produced in the early 1990s and known for its aerodynamic, grille-less front design and improved engineering over its predecessors.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbdc4ce8c81908d143d5451681e6a completed March 7, 2026, 5:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51acc0f88190a580e29d887170ec completed March 9, 2026, 4:50 a.m.
Created at: March 4, 2026, 7:44 p.m.