Triple

T13530268
Position Surface form Disambiguated ID Type / Status
Subject Christian Møller E323113 entity
Predicate familyName P18 FINISHED
Object Møller E323113 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: Møller | Statement: [Christian Møller, familyName, Møller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Møller
Context triple: [Christian Møller, familyName, Møller]
  • A. Hugo Lous Mohr
    Hugo Lous Mohr was a Norwegian painter best known for his monumental church decorations and religious artworks in the early to mid-20th century.
  • B. Nikolaj Malchow-Møller
    Nikolaj Malchow-Møller is a Danish economist and academic leader who serves as the rector of Copenhagen Business School.
  • C. Poul Martin Møller
    Poul Martin Møller was a Danish philosopher, poet, and professor known for his influential contributions to Danish Romanticism and for mentoring the young Søren Kierkegaard.
  • D. Christian Møller chosen
    Christian Møller was a Danish theoretical physicist known for his contributions to quantum electrodynamics and the theory of relativity.
  • E. Georg E.W. Møller
    Georg E.W. Møller was a Danish architect known for designing the Statens Museum for Kunst, Denmark’s national gallery in Copenhagen.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafba2c308190873efd15dfe26358 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7549fc5f881908691eb62c1f5a5d5 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:44 p.m.