Triple

T12566934
Position Surface form Disambiguated ID Type / Status
Subject Province of Westphalia E295497 entity
Predicate containsSettlement P847 FINISHED
Object Schieder-Schwalenberg E779632 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: Schieder-Schwalenberg | Statement: [Province of Westphalia, containsSettlement, Schieder-Schwalenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schieder-Schwalenberg
Context triple: [Province of Westphalia, containsSettlement, Schieder-Schwalenberg]
  • A. Schieder-Schwalenberg chosen
    Schieder-Schwalenberg is a small town in the Lippe district of North Rhine-Westphalia, Germany, known for its historic architecture and scenic location in the Teutoburg Forest region.
  • B. Wülscheid
    Wülscheid is a small locality within the Aegidienberg district of Bad Honnef in North Rhine-Westphalia, Germany.
  • C. Bodersweier
    Bodersweier is a village and district of the town of Kehl in the Ortenaukreis region of Baden-Württemberg, Germany.
  • D. Niederfeld
    Niederfeld is a district within the Mannheim borough of Neckarau in the German state of Baden-Württemberg.
  • E. Sierksdorf
    Sierksdorf is a small coastal municipality in northern Germany, known for its Baltic Sea beaches and the Hansa-Park amusement park.
  • 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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d954a325948190994bcfc9d571a3a8 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f655914f908190afbebbec3cb57e73 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 11:49 p.m.