Triple

T9990199
Position Surface form Disambiguated ID Type / Status
Subject borough of Lichtenberg E196865 entity
Predicate transport P230 FINISHED
Object U-Bahn Berlin E144841 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: U-Bahn Berlin | Statement: [borough of Lichtenberg, transport, U-Bahn Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: U-Bahn Berlin
Context triple: [borough of Lichtenberg, transport, U-Bahn Berlin]
  • A. Berlin U-Bahn chosen
    The Berlin U-Bahn is the German capital’s extensive underground rapid transit system, forming a core part of its public transportation network.
  • B. Berlin S-Bahn
    The Berlin S-Bahn is a rapid transit railway network serving Berlin and its surrounding areas, integrating suburban and urban rail services across the metropolitan region.
  • C. Berlin Stadtbahn
    Berlin Stadtbahn is a major elevated east–west railway corridor in Berlin that carries S-Bahn and regional trains through the city’s central districts.
  • D. Frankfurt U-Bahn
    The Frankfurt U-Bahn is the rapid transit system serving Frankfurt am Main, Germany, forming a core part of the city's public transportation network with multiple underground and surface lines.
  • E. Munich U-Bahn
    The Munich U-Bahn is the German city's rapid transit metro system, forming a core part of its public transportation network with multiple underground lines serving urban and suburban areas.
  • 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_69ca82f1678c819093d06320a05f16a4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdc7a0cb6481908d7bd1b43f93bd18 completed April 2, 2026, 1:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69d26a21b2388190b16f0aa142846599 completed April 5, 2026, 1:56 p.m.
Created at: March 30, 2026, 8:50 p.m.