Triple

T6536626
Position Surface form Disambiguated ID Type / Status
Subject Sunbury line E168179 entity
Predicate usesFareSystem P395 FINISHED
Object Myki E158348 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: Myki | Statement: [Sunbury line, usesFareSystem, Myki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Myki
Context triple: [Sunbury line, usesFareSystem, Myki]
  • A. Myki chosen
    Myki is Melbourne’s contactless smartcard public transport ticketing system used across trains, trams, and buses in Victoria, Australia.
  • B. Opal card
    The Opal card is a reusable, contactless smartcard used to pay for public transport across much of New South Wales, Australia.
  • C. 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.
  • D. TAP card
    The TAP card is a reusable contactless smart card used to pay fares across public transit systems in the Los Angeles County region.
  • E. TransLink card
    The TransLink card was a contactless smart card used for fare payment on public transit systems in the San Francisco Bay Area before being succeeded by the Clipper card.
  • 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_69c68a51564081909e93aee0dbd9cca3 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6adc238688190aca143b22b8a399c completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d53616848190835d9f02bd8e2dbf completed March 27, 2026, 7:06 p.m.
Created at: March 27, 2026, 1:49 p.m.