Triple

T2720861
Position Surface form Disambiguated ID Type / Status
Subject Oyster card E60075 entity
Predicate hasVariant P455 FINISHED
Object Visitor Oyster card E60075 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: Visitor Oyster card | Statement: [Oyster card, hasVariant, Visitor Oyster card]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Visitor Oyster card
Context triple: [Oyster card, hasVariant, Visitor Oyster card]
  • A. Oyster card chosen
    The Oyster card is a rechargeable smartcard used for convenient, cashless payment on public transport services across London.
  • B. ORCA card
    The ORCA card is a reusable, contactless smart card used to pay fares across multiple public transit systems in the Puget Sound region of Washington State.
  • C. Opal card
    The Opal card is a reusable, contactless smartcard used to pay for public transport across much of New South Wales, Australia.
  • D. Travelcard
    Travelcard is a ticketing product used across London’s public transport network, allowing unlimited travel within selected zones on services such as the Underground, buses, and trains.
  • E. Travelcard Zone 5
    Travelcard Zone 5 is an outer London public transport fare zone used to calculate ticket and Travelcard prices on services including the London Underground.
  • 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_69ab4b746d248190958e052045c09255 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdab1cb808190b0789c76bc9cb090 completed March 7, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb6914f70819099482893d026f34b completed March 10, 2026, 6:13 a.m.
Created at: March 6, 2026, 9:55 p.m.