Triple

T25874600
Position Surface form Disambiguated ID Type / Status
Subject Link Belt station E651855 entity
Predicate hasSeptaKeyFareCollection P179183 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: [Link Belt station, hasSeptaKeyFareCollection, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSeptaKeyFareCollection
Context triple: [Link Belt station, hasSeptaKeyFareCollection, yes]
  • A. hasAutomaticFareCollection
    Indicates that an entity is equipped with a system that automatically collects fares or payments from users without manual processing.
  • B. fareSystem
    Indicates a relationship where a system is used to determine, collect, or manage fares or payments for transportation or similar services.
  • C. fareSystemUse
    Indicates the use or application of a particular fare system for travel, ticketing, or pricing.
  • D. hasFareIntegration
    Indicates that two or more transportation services or systems share a coordinated fare structure, allowing passengers to use a single ticket or payment arrangement across them.
  • E. fareSystemFeature
    Indicates that a fare system possesses or supports a particular feature, function, or characteristic related to how fares are calculated, managed, or used.
  • 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_69e7ab3ad9d88190841ddcb93ab02e96 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f7201e241c819092d56a7bb99dc94d completed May 3, 2026, 10:14 a.m.
PD Predicate disambiguation batch_69f71cc405c08190863565609a4c8499 completed May 3, 2026, 10 a.m.
PDg Predicate description generation batch_69f71f8df5d48190944fbfbd9d573868 completed May 3, 2026, 10:12 a.m.
Created at: April 22, 2026, 8:12 a.m.