Triple

T12566798
Position Surface form Disambiguated ID Type / Status
Subject Province of Westphalia E295497 entity
Predicate containsSettlement P847 FINISHED
Object Lippstadt E567830 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: Lippstadt | Statement: [Province of Westphalia, containsSettlement, Lippstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lippstadt
Context triple: [Province of Westphalia, containsSettlement, Lippstadt]
  • A. Lippstadt chosen
    Lippstadt is a historic town in North Rhine-Westphalia, Germany, known for its medieval architecture and role in regional conflicts.
  • B. Remscheid
    Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
  • C. Jülich
    Jülich is a historic town in western Germany, known for its former status as a ducal residence and its significant Renaissance-era fortifications.
  • D. Gardelegen
    Gardelegen is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and its location in the Altmark region.
  • E. Diepholz
    Diepholz is a town in Lower Saxony, Germany, known as a local administrative center and for its surrounding lake district and agricultural landscape.
  • 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_69f76b9383088190a0194cd0e666d11c completed May 3, 2026, 3:36 p.m.
Created at: April 8, 2026, 11:49 p.m.