Triple

T11041582
Position Surface form Disambiguated ID Type / Status
Subject Reeperbahn S-Bahn station E261029 entity
Predicate hasTicketSystem P3383 FINISHED
Object HVV E871899 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: HVV | Statement: [Reeperbahn S-Bahn station, hasTicketSystem, HVV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HVV
Context triple: [Reeperbahn S-Bahn station, hasTicketSystem, HVV]
  • A. HVV
    HVV is the Hamburg public transport association that coordinates and operates regional transit services in and around Hamburg, Germany.
  • B. Metro Service A/S
    Metro Service A/S is the company responsible for operating and managing the Copenhagen Metro system in Denmark.
  • C. Ruter
    Ruter is the public transport authority responsible for planning, coordinating, and managing bus, tram, metro, and some ferry services in Oslo and parts of Viken, Norway.
  • D. Hamburger Verkehrsverbund chosen
    Hamburger Verkehrsverbund is the integrated public transport association serving Hamburg and its surrounding metropolitan region in northern Germany.
  • E. T-bane
    T-bane is the rapid transit metro system serving Oslo and parts of its surrounding metropolitan area in Norway.
  • 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_69d6aa979bdc8190bf0e79104cc098c1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7980050948190ae7b187da5b776ca completed April 9, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a9e525508190bf3a728683eeec79 completed April 18, 2026, 3:57 p.m.
Created at: April 8, 2026, 9:26 p.m.