Triple

T12312916
Position Surface form Disambiguated ID Type / Status
Subject Sumaré E293525 entity
Predicate roadNetworkIntegration P3293 FINISHED
Object state highways of São Paulo 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: state highways of São Paulo | Statement: [Sumaré, roadNetworkIntegration, state highways of São Paulo]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: roadNetworkIntegration
Context triple: [Sumaré, roadNetworkIntegration, state highways of São Paulo]
  • A. streetNetwork
    Indicates the layout and connectivity relationships among streets within a geographic area, including how roads intersect, link, and form a navigable network.
  • B. roadSystem chosen
    Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
  • C. roadNetworkHubOf
    Indicates that one location functions as a central node or hub within the road network relative to another location or area.
  • D. roadNetworkServedBy
    Indicates that a particular road network is provided, maintained, or operated by a specified service, organization, or infrastructure system.
  • E. transportNetwork
    Indicates a relationship where infrastructure or services enable the movement of people or goods between different locations.
  • 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f621570819091ee1db2609233ea completed April 10, 2026, 6:20 p.m.
PD Predicate disambiguation batch_69d93ec02c008190a56aae60a3d9eff6 completed April 10, 2026, 6:17 p.m.
Created at: April 8, 2026, 9:53 p.m.