Triple

T3752181
Position Surface form Disambiguated ID Type / Status
Subject Purple Line (CTA) E81356 entity
Predicate rushHourFeature P26031 FINISHED
Object skips stops between Howard and Belmont during express service 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: skips stops between Howard and Belmont during express service | Statement: [Purple Line (CTA), rushHourFeature, skips stops between Howard and Belmont during express service]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: rushHourFeature
Context triple: [Purple Line (CTA), rushHourFeature, skips stops between Howard and Belmont during express service]
  • A. rushHourServicePattern chosen
    Indicates that a service operates according to a specific pattern or schedule that applies only during rush-hour or peak travel times.
  • B. hasCommuterTraffic
    Indicates that there is regular, recurring traffic flow associated with people traveling between their homes and places of work or study.
  • C. populationPeakPeriod
    Indicates the time period during which a population reached its highest recorded level.
  • D. hasHeavyPassengerTraffic
    Indicates that an entity experiences a high volume of passenger movement or usage over a given period.
  • E. hasPeakHourService
    Indicates that a service operates or is available during designated peak or high-demand hours.
  • 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_69ad8b19b7b08190a6188804e99c53e9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb92135c819093f6d616d3ad28ff completed March 8, 2026, 7:18 p.m.
PD Predicate disambiguation batch_69adc04adebc819088d7f36d0ac343a6 completed March 8, 2026, 6:30 p.m.
Created at: March 8, 2026, 3:35 p.m.