Triple

T13846261
Position Surface form Disambiguated ID Type / Status
Subject Grandview, Texas E332812 entity
Predicate hasRegionalTransportation P941 FINISHED
Object rural road network 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: rural road network | Statement: [Grandview, Texas, hasRegionalTransportation, rural road network]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasRegionalTransportation
Context triple: [Grandview, Texas, hasRegionalTransportation, rural road network]
  • A. hasTransportationSystem chosen
    Indicates that an entity possesses, operates, or is served by an organized system for transporting people or goods.
  • B. transportationRegion
    Indicates that one entity serves as, or is associated with, a geographic region relevant to the transportation activities or coverage of another entity.
  • C. hasPublicTransitFunction
    Indicates that something serves a role or provides a service related to public transportation operations or infrastructure.
  • D. hasTransportRoute
    Indicates that there exists a designated transportation connection or route linking one entity to another.
  • E. hasPublicTransitInfrastructure
    Indicates that a location or area is equipped with facilities and systems that support public transportation services (e.g., buses, trains, trams).
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02b1a25c8190a9f85ba43c421188 completed April 14, 2026, 9:02 a.m.
PD Predicate disambiguation batch_69dbc8691b608190a25a7c70a366b170 completed April 12, 2026, 4:29 p.m.
Created at: April 9, 2026, 10:13 p.m.