Triple

T13389950
Position Surface form Disambiguated ID Type / Status
Subject Coutances E319547 entity
Predicate hasTwinTown P919 FINISHED
Object Hörstel E892783 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: Hörstel | Statement: [Coutances, hasTwinTown, Hörstel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hörstel
Context triple: [Coutances, hasTwinTown, Hörstel]
  • A. Hörstel chosen
    Hörstel is a small town in North Rhine-Westphalia, Germany, known for its location near the Teutoburg Forest and the Dortmund–Ems Canal.
  • B. Hörsel
    Hörsel is a river in central Germany that flows through Thuringia and joins the Werra, contributing to the region’s drainage system.
  • C. Geiersthal
    Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
  • D. Ruppichteroth
    Ruppichteroth is a small municipality in western Germany’s North Rhine-Westphalia region, characterized by its rural setting and proximity to the metropolitan area of Cologne-Bonn.
  • E. Hademstorf
    Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dba0d543348190a9c1be509b015c0f completed April 12, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f73981816881908aac3ab6b1921904 completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:34 p.m.