Triple

T20272979
Position Surface form Disambiguated ID Type / Status
Subject S8 E502936 entity
Predicate network P2637 FINISHED
Object Munich public transport network — NE NERFINISHED

How this triple was built (3 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: Munich public transport network | Statement: [S8, network, Munich public transport network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Munich public transport network
Context triple: [S8, network, Munich public transport network]
  • A. Munich bus network
    The Munich bus network is an extensive public transportation system of bus routes that complements the city’s U-Bahn, S-Bahn, and tram services by providing local and feeder connections across Munich and its suburbs.
  • B. Munich tram network
    The Munich tram network is an extensive street-level light rail system that complements the city’s U-Bahn and S-Bahn by providing dense urban coverage across Munich.
  • C. Berlin public transport network
    The Berlin public transport network is an integrated system of urban and regional trains, trams, buses, and ferries that provides comprehensive mobility across Germany’s capital and its surrounding areas.
  • D. Nuremberg public transport network
    The Nuremberg public transport network is an integrated urban transit system in Nuremberg, Germany, comprising U-Bahn (metro), trams, buses, and regional trains operated under a unified fare and timetable structure.
  • E. Munich S-Bahn
    The Munich S-Bahn is a rapid transit and commuter rail network serving Munich and its surrounding metropolitan region in Bavaria, Germany.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Munich public transport network
Target entity description: The Munich public transport network is an integrated system of S-Bahn, U-Bahn, trams, and buses serving Munich and its surrounding region, coordinated under the Münchner Verkehrs- und Tarifverbund (MVV).
  • A. Munich bus network
    The Munich bus network is an extensive public transportation system of bus routes that complements the city’s U-Bahn, S-Bahn, and tram services by providing local and feeder connections across Munich and its suburbs.
  • B. Munich tram network
    The Munich tram network is an extensive street-level light rail system that complements the city’s U-Bahn and S-Bahn by providing dense urban coverage across Munich.
  • C. Berlin public transport network
    The Berlin public transport network is an integrated system of urban and regional trains, trams, buses, and ferries that provides comprehensive mobility across Germany’s capital and its surrounding areas.
  • D. Nuremberg public transport network
    The Nuremberg public transport network is an integrated urban transit system in Nuremberg, Germany, comprising U-Bahn (metro), trams, buses, and regional trains operated under a unified fare and timetable structure.
  • E. Munich S-Bahn
    The Munich S-Bahn is a rapid transit and commuter rail network serving Munich and its surrounding metropolitan region in Bavaria, Germany.
  • F. None of above. chosen

Provenance (2 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e675dff3c4819098ba45eba4e7b296 completed April 20, 2026, 6:52 p.m.
Created at: April 16, 2026, 10:20 a.m.