Triple

T23215864
Position Surface form Disambiguated ID Type / Status
Subject Troisdorf E580736 entity
Predicate twinTown P1072 FINISHED
Object Genk 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: Genk | Statement: [Troisdorf, twinTown, Genk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Genk
Context triple: [Troisdorf, twinTown, Genk]
  • A. Douai
    Douai is a historic town in northern France known for its medieval belfry, former importance as a university and legal center, and role in the shifting Franco-Flemish borderlands.
  • B. Genk, Belgium chosen
    Genk, Belgium is an industrial city in the province of Limburg known for its former Ford automobile plant and its role as a regional economic and transportation hub.
  • C. Charleroi
    Charleroi is a major industrial city in the Walloon region of Belgium, historically important as a fortified stronghold and later as a center of coal mining and heavy industry.
  • D. Coeuve
    Coeuve is a small rural municipality in the canton of Jura in northwestern Switzerland, near the French border.
  • E. Tervuren
    Tervuren is a municipality in Flemish Brabant, Belgium, known for its historic park, royal connections, and the Royal Museum for Central Africa.
  • 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_69e2460389408190be74f41d217799a9 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f191646c548190a3f7150f0c253dc1 completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:08 p.m.