Triple

T12566827
Position Surface form Disambiguated ID Type / Status
Subject Province of Westphalia E295497 entity
Predicate containsSettlement P847 FINISHED
Object Schwerte E496588 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: Schwerte | Statement: [Province of Westphalia, containsSettlement, Schwerte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwerte
Context triple: [Province of Westphalia, containsSettlement, Schwerte]
  • A. Schwerte chosen
    Schwerte is a town in North Rhine-Westphalia, Germany, known as a small industrial and commuter community near Dortmund.
  • B. Siegburg
    Siegburg is a historic town in North Rhine-Westphalia, Germany, known for its medieval abbey and location near Bonn and Cologne.
  • C. Solingen
    Solingen is a city in western Germany renowned for its centuries-old blade-making tradition and production of high-quality knives and swords.
  • D. Siegen
    Siegen is a city in western Germany known as the birthplace of the Baroque painter Peter Paul Rubens and for its historic mining and university traditions.
  • E. Wehrheim
    Wehrheim is a small municipality in the Hochtaunus district of Hesse, Germany, known for its rural character and proximity to the Taunus mountain range.
  • 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_69f65eb71c548190826d243a354bd01c completed May 2, 2026, 8:29 p.m.
Created at: April 8, 2026, 11:49 p.m.