Triple

T2149257
Position Surface form Disambiguated ID Type / Status
Subject Hauts-de-France E47141 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Nord E70209 NE 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: Nord | Statement: [Hauts-de-France, containsAdministrativeTerritorialEntity, Nord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nord
Context triple: [Hauts-de-France, containsAdministrativeTerritorialEntity, Nord]
  • A. Nord chosen
    Nord is a department in northern France known for its industrial heritage, dense population, and proximity to Belgium.
  • B. Norden
    Norden is a suburban village and residential area within the Metropolitan Borough of Rochdale in Greater Manchester, England.
  • C. Norden
    Norden is a historic coastal town in northern Germany’s East Frisia region, known for its North Sea proximity and traditional Frisian character.
  • D. Vestland
    Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
  • E. Noord
    Noord is a major river in the western Netherlands that forms part of the Rhine–Meuse–Scheldt delta and serves as an important waterway for regional shipping and transport.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a88a1933e0819094f18426ed74180f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe44d2608190986467d43ee224d4 completed March 7, 2026, 5:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae893ade888190980001116e10c874 completed March 9, 2026, 8:47 a.m.
Created at: March 4, 2026, 7:44 p.m.