Triple

T11414587
Position Surface form Disambiguated ID Type / Status
Subject Oyster pay as you go E270456 entity
Predicate cardType P5430 FINISHED
Object 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: Oyster card | Statement: [Oyster pay as you go, cardType, Oyster card]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oyster card
Context triple: [Oyster pay as you go, cardType, 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. Merseytravel smartcard
    The Merseytravel smartcard is a contactless travel card used for seamless payment and ticketing across public transport services in the Merseyside region of England.
  • D. System One travelcards
    System One travelcards are integrated public transport tickets in Greater Manchester that allow unlimited travel across multiple operators and modes within selected zones.
  • E. Metro TAP card
    The Metro TAP card is a reusable, reloadable smart fare card used for contactless payment across the Los Angeles County public transit system.
  • 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_69d6aaddeaa8819088b30ef7b50598c9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d801ae47d0819098123505309c4a68 completed April 9, 2026, 7:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b86936348190b8fa4125995c2a85 completed April 20, 2026, 5:23 a.m.
Created at: April 8, 2026, 9:34 p.m.