Triple

T9470782
Position Surface form Disambiguated ID Type / Status
Subject Schweizer Platz station E228382 entity
Predicate operatedBy P86 FINISHED
Object VGF
VGF is the municipal public transport operator responsible for running Frankfurt am Main’s urban transit network, including its U-Bahn and tram services.
 E800184 NE FINISHED

How this triple was built (4 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: VGF | Statement: [Schweizer Platz station, operatedBy, VGF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VGF
Context triple: [Schweizer Platz station, operatedBy, VGF]
  • A. VGN
    VGN (Verkehrsverbund Großraum Nürnberg) is the public transport association that coordinates and manages integrated ticketing and services across the greater Nuremberg metropolitan area in Germany.
  • B. VG
    VG is the two-letter ISO 3166 country code assigned to the British Virgin Islands.
  • C. VG
    VG is a major Norwegian newspaper and online news outlet known for its wide national readership and influential coverage of current affairs.
  • D. VG
    VG is the vehicle registration code used on license plates for the district of Vorpommern-Greifswald in the German state of Mecklenburg-Vorpommern.
  • E. GVG
    GVG is the standard abbreviation for the German Courts Constitution Act, a key statute that regulates the structure and jurisdiction of the ordinary courts in Germany.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: VGF
Triple: [Schweizer Platz station, operatedBy, VGF]
Generated description
VGF is the municipal public transport operator responsible for running Frankfurt am Main’s urban transit network, including its U-Bahn and tram services.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VGF
Target entity description: VGF is the municipal public transport operator responsible for running Frankfurt am Main’s urban transit network, including its U-Bahn and tram services.
  • A. VGN
    VGN (Verkehrsverbund Großraum Nürnberg) is the public transport association that coordinates and manages integrated ticketing and services across the greater Nuremberg metropolitan area in Germany.
  • B. VG
    VG is the two-letter ISO 3166 country code assigned to the British Virgin Islands.
  • C. VG
    VG is a major Norwegian newspaper and online news outlet known for its wide national readership and influential coverage of current affairs.
  • D. VG
    VG is the vehicle registration code used on license plates for the district of Vorpommern-Greifswald in the German state of Mecklenburg-Vorpommern.
  • E. GVG
    GVG is the standard abbreviation for the German Courts Constitution Act, a key statute that regulates the structure and jurisdiction of the ordinary courts in Germany.
  • F. None of above. chosen

Provenance (5 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_69ca847162c48190b079076c9595513c completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7fee13a88190b4532fb92ddaf401 completed April 1, 2026, 8:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69d122cd0728819088f6c832cd90d832 completed April 4, 2026, 2:40 p.m.
NEDg Description generation batch_69d12350baa08190b08f619391acbd75 completed April 4, 2026, 2:42 p.m.
NED2 Entity disambiguation (via description) batch_69d123af901c819098bb1401846f0daf completed April 4, 2026, 2:43 p.m.
Created at: March 30, 2026, 7:53 p.m.