Triple

T2870446
Position Surface form Disambiguated ID Type / Status
Subject Embarcadero station E63546 entity
Predicate ticketingSystem P3383 FINISHED
Object Clipper card E38241 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: Clipper card | Statement: [Embarcadero station, ticketingSystem, Clipper card]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clipper card
Context triple: [Embarcadero station, ticketingSystem, Clipper card]
  • A. Clipper card chosen
    The Clipper card is a reloadable contactless smart card used to pay fares across multiple public transit systems in the San Francisco Bay Area.
  • B. Presto card
    The Presto card is a reloadable smart card used for paying public transit fares across the Greater Toronto and Hamilton Area and other regions in Ontario, Canada.
  • C. Opal card
    The Opal card is a reusable, contactless smartcard used to pay for public transport across much of New South Wales, Australia.
  • D. Breeze Card
    The Breeze Card is a reusable smart fare card used for paying transit fares across the Metropolitan Atlanta Rapid Transit Authority (MARTA) system in Atlanta, Georgia.
  • E. 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.
  • 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_69ab4c42fb8c8190b36e161d47c03b81 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdfe2dcb48190a194253e733d14af completed March 7, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01db01d348190945ab982ce5c5b2d completed March 10, 2026, 1:33 p.m.
Created at: March 6, 2026, 10:02 p.m.