Triple

T16387761
Position Surface form Disambiguated ID Type / Status
Subject U4 line E397966 entity
Predicate zone P2160 FINISHED
Object Berlin AB E362110 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: Berlin AB | Statement: [U4 line, zone, Berlin AB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin AB
Context triple: [U4 line, zone, Berlin AB]
  • A. Berlin AB chosen
    Berlin AB is the central fare zone of Berlin’s public transport network, covering the inner city and surrounding urban areas served by the Verkehrsverbund Berlin-Brandenburg (VBB).
  • B. Berlin
    Berlin is a major Ethereum network upgrade that introduced various gas cost optimizations and transaction processing improvements to enhance the blockchain’s efficiency and performance.
  • C. Berlin
    Berlin is a borough in Camden County, New Jersey, known as a suburban community within the Philadelphia metropolitan area.
  • D. Berlin
    Berlin is a small town in South Africa’s Eastern Cape province, situated within the Buffalo City Metropolitan Municipality near East London.
  • E. Berlin
    Berlin is the capital and largest city of Germany, historically significant as a focal point of Cold War tensions and a major cultural, political, and economic center in Europe.
  • 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e3263e1534819081a6bf5006c611c5 completed April 18, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00606fe9dc8190a336dc17f16f0ab4 completed May 10, 2026, 10:39 a.m.
Created at: April 10, 2026, 5:08 a.m.