Triple

T2496725
Position Surface form Disambiguated ID Type / Status
Subject Rawtenstall railway station E52167 entity
Predicate hasBookingOffice P39822 FINISHED
Object yes LITERAL 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: yes | Statement: [Rawtenstall railway station, hasBookingOffice, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasBookingOffice
Context triple: [Rawtenstall railway station, hasBookingOffice, yes]
  • A. hasBookingModel
    Indicates that an entity is associated with or uses a particular booking model or reservation scheme.
  • B. hasBookingChannel
    Indicates that an entity is associated with or obtained through a particular method or platform used to make a booking.
  • C. hasFrontDesk
    Indicates that one entity provides or is equipped with a front desk service or reception area for another entity.
  • D. hasOnlineReservation
    Indicates that an entity has a booking or reservation that was made or is managed through an online system.
  • E. hasConferenceSpace
    Indicates that an entity provides or includes dedicated space suitable for holding conferences, meetings, or similar gatherings.
  • F. None of above. chosen

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_69ab4955111c8190835bf619adec21ff completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1abd3688190b5874249e1e333bc completed March 7, 2026, 7:20 a.m.
PD Predicate disambiguation batch_69abd0b980b481908d4932bcea4a6167 completed March 7, 2026, 7:16 a.m.
PDg Predicate description generation batch_69abd1318f7881908a8fc42943df4879 completed March 7, 2026, 7:18 a.m.
Created at: March 6, 2026, 9:45 p.m.