Triple

T14251343
Position Surface form Disambiguated ID Type / Status
Subject Sprockhövel E353269 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Hattingen E195827 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: Hattingen | Statement: [Sprockhövel, hasNeighbouringMunicipality, Hattingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hattingen
Context triple: [Sprockhövel, hasNeighbouringMunicipality, Hattingen]
  • A. Hattingen chosen
    Hattingen is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval old town and its location in the Ruhr industrial region.
  • B. Bergkamen
    Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
  • C. Backworth
    Backworth is a village in North Tyneside, England, historically associated with coal mining and now largely residential.
  • D. Rüdinghausen
    Rüdinghausen is a district of the city of Witten in North Rhine-Westphalia, Germany, characterized by its residential areas and local amenities.
  • E. Schlettstadt
    Schlettstadt, now known as Sélestat, is a historic town in the Alsace region of northeastern France noted for its medieval architecture and humanist heritage.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6296f9d0819086f62f525d07eb12 completed April 14, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda904f8ac8190a4206b6ab6ee812c completed May 8, 2026, 9:12 a.m.
Created at: April 10, 2026, 1:08 a.m.