Triple

T3435573
Position Surface form Disambiguated ID Type / Status
Subject Penarth E72442 entity
Predicate hasTwinTown P919 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: [Penarth, hasTwinTown, Lüdenscheid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lüdenscheid
Context triple: [Penarth, hasTwinTown, 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. Meppen
    Meppen is a historic town in Lower Saxony, Germany, known as a regional center in the Emsland district near the Dutch border.
  • 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. Bentheim
    Bentheim is a historical county in Lower Saxony, Germany, known for its Reformed Protestant heritage and the former County of Bentheim.
  • 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_69ad85af50288190a854b76653deee6f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb9f2e4b4819085336fb539daf3c7 completed March 8, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf185542508190ad71b753bda5d1a3 completed March 21, 2026, 10:14 p.m.
Created at: March 8, 2026, 3:16 p.m.