Triple

T9962170
Position Surface form Disambiguated ID Type / Status
Subject Government of the German-speaking Community E195594 entity
Predicate capital P234 FINISHED
Object Eupen E300219 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: Eupen | Statement: [Government of the German-speaking Community, capital, Eupen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eupen
Context triple: [Government of the German-speaking Community, capital, 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. Bottendorf
    Bottendorf is a locality in the German state of Thuringia that historically existed within the German Empire.
  • C. Izegem
    Izegem is a town in the Belgian province of West Flanders, known historically for its shoe and brush industries.
  • D. 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.
  • E. Durbuy
    Durbuy is a small, picturesque town in the Belgian Ardennes often promoted as one of the “smallest cities in the world,” known for its medieval architecture and tourism.
  • 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_69ca82ebd1288190912f9e4482d1fa35 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb6d37f0c8190946b958c399f3250 completed April 2, 2026, 12:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d794653a948190899e60d18446213a completed April 9, 2026, 11:58 a.m.
Created at: March 30, 2026, 8:47 p.m.