Triple

T23003522
Position Surface form Disambiguated ID Type / Status
Subject Tokyu Bus E572696 entity
Predicate usesTicketingSystem P1740 FINISHED
Object Suica NE NERFINISHED

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: Suica | Statement: [Tokyu Bus, usesTicketingSystem, Suica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suica
Context triple: [Tokyu Bus, usesTicketingSystem, Suica]
  • A. Suica chosen
    Suica is a rechargeable contactless smart card issued by JR East that is widely used for train fares and electronic payments across Japan.
  • B. Kitaca
    Kitaca is a rechargeable contactless smart card used primarily for public transportation and electronic payments in Japan’s Hokkaido region.
  • C. PASMO
    PASMO is a rechargeable contactless smart card widely used for public transportation and electronic payments across the Tokyo metropolitan area.
  • D. ICOCA
    ICOCA is a rechargeable contactless smart card used for fare payment on public transportation systems in the Kansai region of Japan.
  • E. Surutto Kansai Card
    Surutto Kansai Card is a rechargeable smart card used for cashless fare payment on public transportation networks in the Kansai region of Japan.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b6a3ac81908087599eefe3e365 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f183549bdc81908fdcd44e2c92f7c4 completed April 29, 2026, 4:04 a.m.
Created at: April 17, 2026, 3:50 p.m.