Triple

T8554055
Position Surface form Disambiguated ID Type / Status
Subject NS Sprinter E202518 entity
Predicate fareSystem P395 FINISHED
Object OV-chipkaart E28408 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: OV-chipkaart | Statement: [NS Sprinter, fareSystem, OV-chipkaart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OV-chipkaart
Context triple: [NS Sprinter, fareSystem, OV-chipkaart]
  • A. OV-chipkaart chosen
    OV-chipkaart is the nationwide contactless smart card system used for paying public transport fares across the Netherlands.
  • B. Bilhete Único smart card
    The Bilhete Único smart card is São Paulo’s integrated public transport fare card, allowing seamless, discounted transfers across the city’s metro, bus, and train networks.
  • C. OPUS card
    The OPUS card is a reusable, contactless smart card used for public transit fare payment across the greater Montreal area and other regions in Quebec.
  • D. TAP card
    The TAP card is a reusable contactless smart card used to pay fares across public transit systems in the Los Angeles County region.
  • E. Viva Viagem smart card
    The Viva Viagem smart card is a rechargeable contactless travel card used for public transportation across the Lisbon metropolitan area, including metro, buses, trams, and some regional trains.
  • 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_69ca832610e08190b3b6c6cd2c250255 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe8894e7c8190bc0ae2ceec473ecb completed March 31, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6dd67d288190a147562a99ecde56 completed April 2, 2026, 1:23 p.m.
Created at: March 30, 2026, 6:19 p.m.