Triple

T19880614
Position Surface form Disambiguated ID Type / Status
Subject Second Avenue–Broadway Express E477757 entity
Predicate serviceSpeedRelativeToLocal P137684 FINISHED
Object faster than corresponding local services 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: faster than corresponding local services | Statement: [Second Avenue–Broadway Express, serviceSpeedRelativeToLocal, faster than corresponding local services]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: serviceSpeedRelativeToLocal
Context triple: [Second Avenue–Broadway Express, serviceSpeedRelativeToLocal, faster than corresponding local services]
  • A. hasServiceSpeed
    Indicates that an entity provides a service operating at a specified speed or performance rate.
  • B. designedServiceSpeed
    Indicates the intended or specified operational speed at which a service is designed to function.
  • C. serviceLevelComparedToRegional
    Indicates how the service level of one entity compares to the typical or average service level within its surrounding region.
  • D. communicationLatency
    Indicates the time delay between when a communication is sent by one entity and when it is received or processed by another.
  • E. typicalSpeedup
    Indicates the usual or expected performance improvement (e.g., reduction in time or increase in speed) achieved when applying one method, system, or configuration relative to another.
  • 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_69d8e51f32b08190b3687f4f60353250 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e658de4b288190a41bee67f570be1e completed April 20, 2026, 4:48 p.m.
PD Predicate disambiguation batch_69e537e8c4e481909fe95d795b4864e7 completed April 19, 2026, 8:15 p.m.
PDg Predicate description generation batch_69e543c136b081909cab9394b958390a completed April 19, 2026, 9:06 p.m.
Created at: April 10, 2026, 1:52 p.m.