Triple

T3661249
Position Surface form Disambiguated ID Type / Status
Subject LIRR City Terminal Zone E77652 entity
Predicate fareZoneNumber P49359 FINISHED
Object 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: 1 | Statement: [LIRR City Terminal Zone, fareZoneNumber, 1]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fareZoneNumber
Context triple: [LIRR City Terminal Zone, fareZoneNumber, 1]
  • A. hasFareZoneCode chosen
    Indicates that an entity is associated with a specific fare zone identifier used for pricing or tariff purposes.
  • B. hasFareZone
    Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
  • C. fareSystem
    Indicates a relationship where a system is used to determine, collect, or manage fares or payments for transportation or similar services.
  • D. hasFareZoneFeature
    Indicates that an entity is associated with a specific fare zone or fare-related area designation.
  • E. fareControlLocation
    Indicates a location where access to or use of a transportation service is regulated, checked, or controlled for fare payment.
  • 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_69ad85dfc4dc8190a441864202ab2a7a completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc3d6fa188190a6db5bdae7083573 completed March 8, 2026, 6:45 p.m.
PD Predicate disambiguation batch_69adb847e9d881909dad2ffd0f3b6c15 completed March 8, 2026, 5:56 p.m.
Created at: March 8, 2026, 3:25 p.m.