Triple

T13105220
Position Surface form Disambiguated ID Type / Status
Subject Travelcard Zone 4 E310826 entity
Predicate adjacentTo P224 FINISHED
Object Travelcard Zone 5 E289783 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 Zone 5 | Statement: [Travelcard Zone 4, adjacentTo, Travelcard Zone 5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Travelcard Zone 5
Context triple: [Travelcard Zone 4, adjacentTo, Travelcard Zone 5]
  • A. Travelcard Zone 5 chosen
    Travelcard Zone 5 is an outer London public transport fare zone used to calculate ticket and Travelcard prices on services including the London Underground.
  • B. 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.
  • C. Travelcard Zone 8
    Travelcard Zone 8 is one of the outer fare zones of the London public transport system, covering several suburban and commuter towns beyond the city’s central area.
  • D. Travelcard Zone 7
    Travelcard Zone 7 is one of the outer fare zones of the London public transport system, covering several suburban and fringe areas beyond the central city.
  • E. Travelcard Zone 4
    Travelcard Zone 4 is a London public transport fare zone covering suburban areas beyond the inner city, used to calculate ticket and Travelcard prices on services including the Underground.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98154c9f48190aeca779d97151759 completed April 10, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5cd9f2081908c207b21a14233e1 completed May 3, 2026, 7:14 a.m.
Created at: April 9, 2026, 9:05 p.m.