Triple

T15494293
Position Surface form Disambiguated ID Type / Status
Subject King William Street, London E378773 entity
Predicate streetNumberingSystem P49387 FINISHED
Object buildings numbered sequentially along both sides 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: buildings numbered sequentially along both sides | Statement: [King William Street, London, streetNumberingSystem, buildings numbered sequentially along both sides]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: streetNumberingSystem
Context triple: [King William Street, London, streetNumberingSystem, buildings numbered sequentially along both sides]
  • A. hasStreetNumberingSystem chosen
    Indicates that a location or area uses an organized system for assigning numbers to buildings or addresses along its streets.
  • B. hasRoadNumberSystem
    Indicates that a place or region uses a specific system for assigning numbers to its roads or highways.
  • C. hasJunctionNumbering
    Indicates that a road or route is assigned a specific numbering system for its junctions or intersections.
  • D. postalCodeSystem
    Indicates a system that assigns structured postal codes to geographic areas for organizing and routing mail.
  • E. roadNumberType
    Indicates the classification or type category assigned to a road’s identifying number (e.g., highway, route, local road).
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fad723481908d2aa33e8f065f2f completed April 16, 2026, 1:47 a.m.
PD Predicate disambiguation batch_69ded2874b788190999158e0f043be21 completed April 14, 2026, 11:49 p.m.
Created at: April 10, 2026, 3:49 a.m.