Triple

T3374520
Position Surface form Disambiguated ID Type / Status
Subject Blackfriars station E71034 entity
Predicate ticketingSystem P3383 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: [Blackfriars station, ticketingSystem, Oyster card]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oyster card
Context triple: [Blackfriars station, ticketingSystem, 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 Zone 1
    Travelcard Zone 1 is the central London fare zone covering the city’s core Underground and rail stations, including many major commercial, tourist, and transport hubs.
  • E. MetroCard
    MetroCard is a magnetic stripe payment card formerly used as the primary method for paying fares on New York City’s public transit system, including subways and buses.
  • 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_69ad85a7f80c8190a05e43013f298942 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb2bf4ad88190a2c49dc30f323a13 completed March 8, 2026, 5:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b33442f28c8190b48a662a5dd1bac3 completed March 12, 2026, 9:46 p.m.
Created at: March 8, 2026, 3:13 p.m.