Triple

T23200
Position Surface form Disambiguated ID Type / Status
Subject Belmont Center station E461 entity
Predicate fareZone P844 FINISHED
Object Zone 1 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: Zone 1 | Statement: [Belmont Center station, fareZone, Zone 1]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fareZone
Context triple: [Belmont Center station, fareZone, Zone 1]
  • A. fareSystem
    Indicates a relationship where a system is used to determine, collect, or manage fares or payments for transportation or similar services.
  • B. hasFareZone chosen
    Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
  • C. FIPSCode
    Indicates the standardized Federal Information Processing Standards (FIPS) code assigned to identify a specific geographic or administrative entity.
  • D. publicTransit
    Indicates that one entity provides or is connected via shared, scheduled transportation services (such as buses, trains, or subways) that are available for use by the general public.
  • E. hasRegion
    Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
  • F. None of above.

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_69a243b4ac2c8190b93c303df797b7b2 completed Feb. 28, 2026, 1:24 a.m.
NER Named-entity recognition batch_69a246e94ca881908f7a7d2c0b293033 completed Feb. 28, 2026, 1:37 a.m.
PD Predicate disambiguation batch_69a246560af88190961ea00b35cf9388 completed Feb. 28, 2026, 1:35 a.m.
Created at: Feb. 28, 2026, 1:34 a.m.