Triple

T13295450
Position Surface form Disambiguated ID Type / Status
Subject Travelcard Zones 1–5 E316668 entity
Predicate usedFor P98 FINISHED
Object 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: Travelcard | Statement: [Travelcard Zones 1–5, usedFor, Travelcard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Travelcard
Context triple: [Travelcard Zones 1–5, usedFor, 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. Travelcard Zone 9
    Travelcard Zone 9 is one of the outermost London fare zones, covering certain suburban and out-of-London railway stations for Travelcard and contactless ticketing.
  • C. Travelcard Zone 6
    Travelcard Zone 6 is one of the outer fare zones in the London public transport system, covering suburban areas on the edge of Greater London.
  • D. System One travelcards
    System One travelcards are integrated public transport tickets in Greater Manchester that allow unlimited travel across multiple operators and modes within selected zones.
  • E. Travelcard Zone 3
    Travelcard Zone 3 is a ring of suburban areas in London used for calculating fares on public transport services such as the Underground, Overground, and buses.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99079c8508190b6208db9affcbc0e completed April 11, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716dad3648190bf360955fbdfb2f0 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:28 p.m.