Triple

T19507408
Position Surface form Disambiguated ID Type / Status
Subject Mill en Sint Hubert E488058 entity
Predicate containsSettlement P847 FINISHED
Object Langenboom NE NERFINISHED

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: Langenboom | Statement: [Mill en Sint Hubert, containsSettlement, Langenboom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Langenboom
Context triple: [Mill en Sint Hubert, containsSettlement, Langenboom]
  • A. Langenboom chosen
    Langenboom is a village in the Dutch province of North Brabant, known as a small rural community within the municipality of Mill en Sint Hubert.
  • B. Bommershoven
    Bommershoven is a village in the Belgian province of Limburg that forms one of the municipal sections of the city of Borgloon.
  • C. Uithoorn
    Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
  • D. Groesbeek
    Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
  • E. Vinkeveen
    Vinkeveen is a Dutch village in the province of Utrecht, best known for its lakes and recreational water activities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e635130e708190bb3d70e1abbade2a completed April 20, 2026, 2:15 p.m.
Created at: April 10, 2026, 1:40 p.m.