Triple

T7506576
Position Surface form Disambiguated ID Type / Status
Subject Münsterland E177404 entity
Predicate hasCity P316 FINISHED
Object Bocholt E690887 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: Bocholt | Statement: [Münsterland, hasCity, Bocholt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bocholt
Context triple: [Münsterland, hasCity, Bocholt]
  • A. Bocholt
    Bocholt is a municipality in the Belgian province of Limburg, known for its rural character and local brewing tradition.
  • B. Bocholt chosen
    Bocholt is a medium-sized German city in the state of North Rhine-Westphalia, known for its industrial heritage and proximity to the Dutch border.
  • 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. Remscheid
    Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
  • E. Herzogenrath
    Herzogenrath is a town in western Germany near the Dutch border, known for its cross-border cooperation with the neighboring Dutch town of Kerkrade.
  • 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_69c69f276b108190af2cc790b6554544 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5b76a288190bb3608a5e3bfa212 completed March 27, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69cbde8e8264819082a3954072dffd09 completed March 31, 2026, 2:47 p.m.
Created at: March 27, 2026, 3:45 p.m.