Triple

T7732103
Position Surface form Disambiguated ID Type / Status
Subject Soest E175283 entity
Predicate hasSubdivision P747 FINISHED
Object Soest-Mitte E175283 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: Soest-Mitte | Statement: [Soest, hasSubdivision, Soest-Mitte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Soest-Mitte
Context triple: [Soest, hasSubdivision, Soest-Mitte]
  • A. Soest chosen
    Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
  • B. Soest
    Soest is a Dutch town and municipality in the central Netherlands known for its green surroundings and proximity to the Utrechtse Heuvelrug.
  • C. Soest district
    Soest district is a rural administrative district (Kreis) in the German state of North Rhine-Westphalia, known for its historic towns, agricultural landscape, and location between the Ruhr area and the Sauerland region.
  • D. Rudolfswerth
    Rudolfswerth is the former German name for Novo Mesto, a historic town in southeastern Slovenia known for its medieval heritage and role as a regional cultural center.
  • E. Duisdorf
    Duisdorf is a district of Bonn, Germany, known as a residential area with local commerce and public services within the borough of Hardtberg.
  • 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70336aafc819099a060950ab8922f completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b531a7f481908e4ff7f15b851070 completed March 29, 2026, 5:14 a.m.
Created at: March 27, 2026, 4:06 p.m.