Triple

T16177080
Position Surface form Disambiguated ID Type / Status
Subject Zürcher Verkehrsverbund E392591 entity
Predicate shortName P43 FINISHED
Object ZVV E390723 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: ZVV | Statement: [Zürcher Verkehrsverbund, shortName, ZVV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ZVV
Context triple: [Zürcher Verkehrsverbund, shortName, ZVV]
  • A. ZVV chosen
    ZVV is the Zürcher Verkehrsverbund, the integrated public transport network and fare association for the Zurich metropolitan area in Switzerland.
  • B. ZVVZ
    ZVVZ is a Czech industrial company known for producing air-handling, filtration, and environmental technology equipment.
  • C. D-Zug
    D-Zug was a former class of fast long-distance passenger trains in German-speaking countries, known for providing relatively quick intercity connections before being largely superseded by newer service categories.
  • D. EV Zug
    EV Zug is a professional ice hockey club from Zug, Switzerland, known as one of the prominent teams in the country’s top-tier league.
  • E. HVV
    HVV is the Hamburg public transport association that coordinates and operates regional transit services in and around Hamburg, Germany.
  • 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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e22059e7048190b4592cb1516b5f8d completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7c11bc881909211a668f48092aa completed May 10, 2026, 3:13 a.m.
Created at: April 10, 2026, 5:02 a.m.