Triple

T19639653
Position Surface form Disambiguated ID Type / Status
Subject Lena Meijer E471495 entity
Predicate hasNameInNativeLanguage P1435 FINISHED
Object Lena Meijer 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: Lena Meijer | Statement: [Lena Meijer, hasNameInNativeLanguage, Lena Meijer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lena Meijer
Context triple: [Lena Meijer, hasNameInNativeLanguage, Lena Meijer]
  • A. Lena Meijer chosen
    Lena Meijer was an American philanthropist and co-founder of the Meijer supermarket chain, known for her extensive charitable contributions to education, health, and the arts, particularly in Michigan.
  • B. Ria Lubbers
    Ria Lubbers is best known as the wife of former Dutch Prime Minister Ruud Lubbers and as a public figure who supported his long political career.
  • C. Nicole de Boer
    Nicole de Boer is a Canadian actress best known for playing Ezri Dax on the television series Star Trek: Deep Space Nine.
  • D. Maayke Velders
    Maayke Velders is known primarily as the spouse of Dutch naval hero Michiel de Ruyter.
  • E. Saskia de Jonge
    Saskia de Jonge is a Dutch former competitive swimmer who specialized in freestyle events and represented the Netherlands in international competitions, including the Olympic Games.
  • 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_69d8e511f28481909f4bc3ea9191e54a completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e641215df48190926b38e6502bb83e completed April 20, 2026, 3:07 p.m.
Created at: April 10, 2026, 1:44 p.m.