Triple

T11126898
Position Surface form Disambiguated ID Type / Status
Subject ZIL MCC station E263161 entity
Predicate hasTicketingSystem P3383 FINISHED
Object Troika card compatible E249223 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: Troika card compatible | Statement: [ZIL MCC station, hasTicketingSystem, Troika card compatible]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Troika card compatible
Context triple: [ZIL MCC station, hasTicketingSystem, Troika card compatible]
  • A. Troika card chosen
    The Troika card is a reusable contactless smart card used for paying fares across Moscow’s public transportation system.
  • B. ConnectCard
    ConnectCard is a reusable smart fare card used by Pittsburgh Regional Transit riders to pay for public transportation across the Pittsburgh area.
  • C. 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.
  • D. Eurocard
    Eurocard is a standardized modular printed circuit board format widely used in industrial, telecommunications, and computing systems for plug-in electronic assemblies.
  • E. Leap Card
    Leap Card is a reusable, contactless smart card used for paying public transport fares across Dublin and other parts of Ireland.
  • 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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7e82fc5f88190b34c55de3d50f6a7 completed April 9, 2026, 5:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69e441dcb4608190a4cfa46c194d11ae completed April 19, 2026, 2:45 a.m.
Created at: April 8, 2026, 9:28 p.m.