Triple

T11312822
Position Surface form Disambiguated ID Type / Status
Subject Bishopric of Lüdenscheid E267882 entity
Predicate capital P234 FINISHED
Object Lüdenscheid E344748 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: Lüdenscheid | Statement: [Bishopric of Lüdenscheid, capital, Lüdenscheid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lüdenscheid
Context triple: [Bishopric of Lüdenscheid, capital, Lüdenscheid]
  • A. Lüdenscheid chosen
    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.
  • B. Schwelm
    Schwelm is a small town in North Rhine-Westphalia, Germany, known as the administrative seat of the Ennepe-Ruhr district.
  • C. Dülmen
    Dülmen is a town in western Germany’s North Rhine-Westphalia, known for its location between Münster and the Ruhr area and for the wild Dülmen ponies in the nearby nature reserve.
  • D. Meppen
    Meppen is a historic town in Lower Saxony, Germany, known as a regional center in the Emsland district near the Dutch border.
  • E. Bocholt
    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.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c1b7dc81908d8cc768c47390d3 completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f489dfb2c881908a6f6bcd8b2d1cdc completed May 1, 2026, 11:09 a.m.
Created at: April 8, 2026, 9:32 p.m.