Triple

T509941
Position Surface form Disambiguated ID Type / Status
Subject Prussia E10584 entity
Predicate capital P234 FINISHED
Object Königsberg E19236 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: Königsberg | Statement: [Prussia, capital, Königsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Königsberg
Context triple: [Prussia, capital, Königsberg]
  • A. Königsberg chosen
    Königsberg was a historic Prussian city on the Baltic Sea, renowned as a major cultural and intellectual center of East Prussia and later known as Kaliningrad.
  • B. Potsdam
    Potsdam is a historic German city near Berlin, known for its palaces, parks, and role in major 20th-century diplomatic events.
  • C. Borsigwalde
    Borsigwalde is a residential locality in the Berlin borough of Reinickendorf, known for its industrial heritage linked to the Borsig engineering works.
  • D. Cölln
    Cölln was a historic town on the River Spree that, together with Berlin, formed the core of what later became the city of Berlin.
  • E. Brest
    Brest is a major port city in northwestern France that serves as one of the country’s principal naval and maritime centers.
  • 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_69a2e848adf881908e5e04f7af030093 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f164a9d48190b525a97b5c06ffe2 completed Feb. 28, 2026, 1:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6373fbf388190afb01fcfd67f03bf completed March 3, 2026, 1:19 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.