Triple

T4475238
Position Surface form Disambiguated ID Type / Status
Subject Northwood, London E99991 entity
Predicate stationZone P2160 FINISHED
Object Travelcard Zone 6 E301952 NE FINISHED

How this triple was built (3 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 6 | Statement: [Northwood, London, stationZone, Travelcard Zone 6]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Travelcard Zone 6
Context triple: [Northwood, London, stationZone, Travelcard Zone 6]
  • A. Travelcard Zone 6 chosen
    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.
  • B. Travelcard Zone 5
    Travelcard Zone 5 is an outer London public transport fare zone used to calculate ticket and Travelcard prices on services including the London Underground.
  • C. 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.
  • D. 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.
  • E. Travelcard Zones 1–5
    Travelcard Zones 1–5 are a set of concentric public transport fare zones in London covering central and much of suburban Greater London for use on services such as the Underground, buses, and trains.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: stationZone
Context triple: [Northwood, London, stationZone, Travelcard Zone 6]
  • A. stationComplex
    Indicates a relationship where one entity is a station complex that encompasses or is associated with another station-related entity.
  • B. zone chosen
    Indicates that an entity is located within, associated with, or assigned to a particular geographic or conceptual area or zone.
  • C. ownedStation
    Indicates that one entity possesses ownership or control over a particular station.
  • D. stationName
    Indicates the name assigned to a particular station in the relationship.
  • E. stationType
    Indicates the specific category or classification of a station based on its function, services, or operational characteristics.
  • F. None of above.

Provenance (4 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_69b34553cbe48190afa8ac1cac285b86 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35728ed508190ba0e882fa62d8848 completed March 13, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6287f076081909bca3643ac489fcf completed March 15, 2026, 3:33 a.m.
PD Predicate disambiguation batch_69b3563d63008190816e37027e761375 completed March 13, 2026, 12:11 a.m.
Created at: March 12, 2026, 11:35 p.m.