Triple

T6793649
Position Surface form Disambiguated ID Type / Status
Subject South Limburg E155996 entity
Predicate contains P35 FINISHED
Object Vaalserberg E124686 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: Vaalserberg | Statement: [South Limburg, contains, Vaalserberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vaalserberg
Context triple: [South Limburg, contains, Vaalserberg]
  • A. Vaalserberg chosen
    Vaalserberg is a hill in the southeastern Netherlands known as the country's highest point and the location of the tripoint where the borders of the Netherlands, Germany, and Belgium meet.
  • B. Mount Van Hoevenberg
    Mount Van Hoevenberg is a mountain in New York’s Adirondack region best known for its winter sports facilities and role in hosting events for the 1932 and 1980 Winter Olympics.
  • C. Nuweveldberge
    Nuweveldberge is a mountain range in South Africa that forms part of the Great Escarpment and is known for its rugged terrain and semi-arid Karoo landscapes.
  • D. Bonteheuwel
    Bonteheuwel is a residential suburb of Cape Town, South Africa, located on the Cape Flats and known for its working-class community and apartheid-era history.
  • E. Wilgeheuwel
    Wilgeheuwel is a residential suburb in the Roodepoort area of Johannesburg, South Africa, known for its modern housing developments and proximity to major urban amenities.
  • 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_69c6881844448190a65822d9b39d7f88 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2af6f908190809e39b73894e513 completed March 27, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a90dfb081909120e8502b26a88b completed March 28, 2026, 12:02 a.m.
Created at: March 27, 2026, 2:15 p.m.