Triple

T10167509
Position Surface form Disambiguated ID Type / Status
Subject 116th Street–Columbia University E235242 entity
Predicate hasFareControlAtStreet P1973 FINISHED
Object no 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: no | Statement: [116th Street–Columbia University, hasFareControlAtStreet, no]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFareControlAtStreet
Context triple: [116th Street–Columbia University, hasFareControlAtStreet, no]
  • A. hasFareControlIntegrationSince
    Indicates that a fare control system has been integrated with another system or entity starting from a specific point in time.
  • B. fareControlUnifiedWith
    Indicates that separate fare control areas are combined into a single, shared fare-controlled zone.
  • C. fareControl
    Indicates that an entity is responsible for monitoring, enforcing, or managing payment of fares for access to a service or facility.
  • D. hasFaregates chosen
    Indicates that an entity is equipped with or contains faregates used to control or validate access, typically for paid entry.
  • E. hasFareZoneSystem
    Indicates that an entity uses or is associated with a particular fare zone system for determining travel costs or ticketing.
  • 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_69ca84ceafd0819085828600e11bed6b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec6e016c81909ded2a16b839c405 completed April 2, 2026, 4:11 a.m.
PD Predicate disambiguation batch_69cd4ba9956c8190a3e15d091e33149d completed April 1, 2026, 4:45 p.m.
Created at: March 30, 2026, 9:10 p.m.