Triple

T3595783
Position Surface form Disambiguated ID Type / Status
Subject Hankyu Railway E76136 entity
Predicate smartCardSystem P35327 FINISHED
Object ICOCA E71900 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: ICOCA | Statement: [Hankyu Railway, smartCardSystem, ICOCA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ICOCA
Context triple: [Hankyu Railway, smartCardSystem, ICOCA]
  • A. ICOCA chosen
    ICOCA is a rechargeable contactless smart card used for fare payment on public transportation systems in the Kansai region of Japan.
  • B. Suica
    Suica is a rechargeable contactless smart card issued by JR East that is widely used for train fares and electronic payments across Japan.
  • C. Kitaca
    Kitaca is a rechargeable contactless smart card used primarily for public transportation and electronic payments in Japan’s Hokkaido region.
  • D. PASMO
    PASMO is a rechargeable contactless smart card widely used for public transportation and electronic payments across the Tokyo metropolitan area.
  • E. 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.
  • 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_69ad85d8042081908af94a04c410dec0 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc15f41cc819085b3e897d823757d completed March 8, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b403130cf081909bb90800d7dc2d6f completed March 13, 2026, 12:29 p.m.
Created at: March 8, 2026, 3:22 p.m.