Triple

T465590
Position Surface form Disambiguated ID Type / Status
Subject Angela Dorothea Kasner E8439 entity
Predicate middleName P143 FINISHED
Object Dorothea E10813 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: Dorothea | Statement: [Angela Dorothea Kasner, middleName, Dorothea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dorothea
Context triple: [Angela Dorothea Kasner, middleName, Dorothea]
  • A. Dorothea chosen
    Dorothea is the middle name of Angela Merkel, the long-serving former chancellor of Germany.
  • B. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • C. Bathsheba
    Bathsheba is a prominent biblical figure known as the wife of King David and the mother of King Solomon.
  • D. Sophia Julian
    Sophia Julian was the wife of prominent American labor leader Samuel Gompers and a supportive figure in his personal and family life.
  • E. Sophia
    Sophia of the Palatinate was a 17th-century German princess and Electress of Hanover, best known as the mother of King George I of Great Britain and a key figure in the Protestant succession to the British throne.
  • 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_69a2e7f3aeb48190a19453e3a043f486 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2efd6ec708190b78c7f22deb3ca64 completed Feb. 28, 2026, 1:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69a452985bb48190890711440edcf598 completed March 1, 2026, 2:52 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.