Triple

T7852461
Position Surface form Disambiguated ID Type / Status
Subject Shinjuku-sanchome Station E182087 entity
Predicate acceptsCard P15672 FINISHED
Object Suica E131332 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: Suica | Statement: [Shinjuku-sanchome Station, acceptsCard, Suica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suica
Context triple: [Shinjuku-sanchome Station, acceptsCard, 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. Myki
    Myki is Melbourne’s contactless smartcard public transport ticketing system used across trains, trams, and buses in Victoria, Australia.
  • 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_69ca82869ee08190b8f9040dbc2c0467 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb18ec48548190960bd564a60effa8 completed March 31, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5b161a4881909641f3a29c1650b4 completed March 31, 2026, 5:26 a.m.
Created at: March 30, 2026, 4:51 p.m.