Triple

T7407593
Position Surface form Disambiguated ID Type / Status
Subject Dillenburg E170913 entity
Predicate twinTown P1072 FINISHED
Object Herzogenrath E693691 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: Herzogenrath | Statement: [Dillenburg, twinTown, Herzogenrath]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herzogenrath
Context triple: [Dillenburg, twinTown, Herzogenrath]
  • A. Herzogenrath chosen
    Herzogenrath is a town in western Germany near the Dutch border, known for its cross-border cooperation with the neighboring Dutch town of Kerkrade.
  • B. Remscheid
    Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
  • C. Lüdenscheid
    Lüdenscheid is a town in western Germany’s Sauerland region, historically noted for its role in World War II and known today for its metal and plastics industries.
  • D. Euskirchen
    Euskirchen is a town in the German state of North Rhine-Westphalia, known as a regional center near Bonn and the Eifel region.
  • E. Datteln
    Datteln is a town in North Rhine-Westphalia, Germany, known for its canal junction and industrial heritage.
  • 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_69c68a6010108190925e5284de022660 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f298f2388190afc944c9bc78749a completed March 27, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb59ca4c088190bc4f1f9b2488d996 completed March 31, 2026, 5:21 a.m.
Created at: March 27, 2026, 3:10 p.m.