Triple

T16919840
Position Surface form Disambiguated ID Type / Status
Subject Grenzallee E410415 entity
Predicate hasTicketZone P844 FINISHED
Object VBB Berlin A E312736 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: VBB Berlin A | Statement: [Grenzallee, hasTicketZone, VBB Berlin A]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VBB Berlin A
Context triple: [Grenzallee, hasTicketZone, VBB Berlin A]
  • A. VBB: Berlin AB chosen
    VBB: Berlin AB is the central fare zone of Berlin’s public transport network, covering the inner city area served by buses, trams, U-Bahn, and S-Bahn.
  • B. BVB
    BVB is the public transport company that operates much of the tram and bus network in Basel, Switzerland.
  • C. BVB
    BVB is the common abbreviation for Borussia Dortmund, a major professional football club based in Dortmund, Germany.
  • D. Berliner Fußball-Verband
    The Berliner Fußball-Verband is the regional football association responsible for organizing and overseeing football activities and competitions in Berlin, Germany.
  • E. VBB
    VBB is the public transport authority and fare network that coordinates and integrates regional and urban transit services across Berlin and the surrounding Brandenburg region.
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cded2f8481909a20cc08b47e922e completed April 18, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7c2c9cc8190b6d59d0a8edd078d completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:30 a.m.