Triple

T7217899
Position Surface form Disambiguated ID Type / Status
Subject Daegu Metro E150181 entity
Predicate smartCardSystem P35327 FINISHED
Object Cashbee E467237 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: Cashbee | Statement: [Daegu Metro, smartCardSystem, Cashbee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cashbee
Context triple: [Daegu Metro, smartCardSystem, Cashbee]
  • A. Cashbee card chosen
    The Cashbee card is a rechargeable contactless smart card widely used in South Korea for paying public transportation fares and small retail purchases.
  • B. DreamPay
    DreamPay is a digital payments and financial services brand associated with Indian fantasy sports company Dream Sports.
  • C. Paymer
    Paymer is a surname most notably associated with American character actor David Paymer, known for his extensive work in film and television.
  • D. WePay
    WePay is an online payment services company that provides integrated payment processing solutions for platforms, marketplaces, and software providers.
  • E. Rosaire Paiement
    Rosaire Paiement is a former Canadian professional ice hockey forward who played in the NHL during the 1960s and 1970s, notably for teams such as the Philadelphia Flyers and Vancouver Canucks.
  • 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_69c687effb44819092b95d07d0368c9f completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6e99170d88190b1aef326a7d81134 completed March 27, 2026, 8:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cbfb46388190992cc98039e71748 completed March 28, 2026, 12:39 p.m.
Created at: March 27, 2026, 2:53 p.m.