Triple

T12566882
Position Surface form Disambiguated ID Type / Status
Subject Province of Westphalia E295497 entity
Predicate containsSettlement P847 FINISHED
Object Kierspe E288041 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: Kierspe | Statement: [Province of Westphalia, containsSettlement, Kierspe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kierspe
Context triple: [Province of Westphalia, containsSettlement, Kierspe]
  • A. Yerseke
    Yerseke is a Dutch village in the province of Zeeland, best known for its mussel and oyster farming along the Eastern Scheldt.
  • B. Bergeijk
    Bergeijk is a municipality and village in the southern Netherlands, located in the province of North Brabant near the Belgian border.
  • C. Heiligenhaus chosen
    Heiligenhaus is a small town in North Rhine-Westphalia, western Germany, known for its manufacturing industry and location between Düsseldorf and Essen.
  • D. Hansweert
    Hansweert is a small village in the Dutch province of Zeeland, known historically as a canal and shipping hub along the Western Scheldt.
  • E. Geldern
    Geldern is a historic town in western Germany, notable as the namesake and former center of the medieval Duchy of Guelders.
  • 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.