Triple

T2634420
Position Surface form Disambiguated ID Type / Status
Subject Travelcard E59709 entity
Predicate hasConcessionVariant P455 FINISHED
Object Child Travelcard E59709 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: Child Travelcard | Statement: [Travelcard, hasConcessionVariant, Child Travelcard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Child Travelcard
Context triple: [Travelcard, hasConcessionVariant, Child Travelcard]
  • A. Travelcard chosen
    Travelcard is a ticketing product used across London’s public transport network, allowing unlimited travel within selected zones on services such as the Underground, buses, and trains.
  • B. Oyster card
    The Oyster card is a rechargeable smartcard used for convenient, cashless payment on public transport services across London.
  • C. ScotRail smartcard
    The ScotRail smartcard is a reusable contactless travel card that allows passengers to store and use train tickets electronically across Scotland’s rail network.
  • 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. 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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abdd1ca0248190aa15f80b2798524e completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69af90ac94d48190b3138abac9934ec8 completed March 10, 2026, 3:31 a.m.
Created at: March 6, 2026, 9:50 p.m.