Triple

T19807536
Position Surface form Disambiguated ID Type / Status
Subject Rur E475853 entity
Predicate flowsThrough P225 FINISHED
Object Eupen NE NERFINISHED

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: Eupen | Statement: [Rur, flowsThrough, Eupen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eupen
Context triple: [Rur, flowsThrough, Eupen]
  • A. Eupen chosen
    Eupen is a town in eastern Belgium that serves as the administrative center of the country’s German-speaking Community.
  • B. Eupen-Malmedy
    Eupen-Malmedy is a historically contested, predominantly German-speaking border region that was transferred from Germany to Belgium after World War I and remains part of eastern Belgium today.
  • C. Bottendorf
    Bottendorf is a locality in the German state of Thuringia that historically existed within the German Empire.
  • D. Izegem
    Izegem is a town in the Belgian province of West Flanders, known historically for its shoe and brush industries.
  • E. Vilvoorde
    Vilvoorde is a city in the Flemish Region of Belgium, located just north of Brussels and known as part of the capital’s broader metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51bc4208190a1c57d8c5d1b15e4 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65428f5c48190be6ae0d6a77675d2 completed April 20, 2026, 4:28 p.m.
Created at: April 10, 2026, 1:49 p.m.