Triple

T10921639
Position Surface form Disambiguated ID Type / Status
Subject Mark Obama Ndesandjo E257959 entity
Predicate mother P120 FINISHED
Object Ruth Nidesand E260278 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: Ruth Nidesand | Statement: [Mark Obama Ndesandjo, mother, Ruth Nidesand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ruth Nidesand
Context triple: [Mark Obama Ndesandjo, mother, Ruth Nidesand]
  • A. Ruth Nidesand chosen
    Ruth Nidesand is a woman known primarily for her familial connection to Mark Obama Ndesandjo, the American businessman and author who is a half-brother of former U.S. President Barack Obama.
  • B. Edith Schippers
    Edith Schippers is a Dutch politician who served as Minister of Health, Welfare and Sport and is a prominent member of the People's Party for Freedom and Democracy (VVD).
  • C. Hilda Koopman
    Hilda Koopman is a prominent linguist known for her influential work in syntactic theory and generative grammar.
  • D. Judith van Leeuwen
    Judith van Leeuwen was the wife of Dutch Golden Age painter and mezzotint engraver Jan Verkolje.
  • E. Emily Damstra
    Emily Damstra is a Canadian-born scientific illustrator and coin designer known for her detailed nature-themed artwork for the U.S. Mint and other institutions.
  • 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d77082a1488190850a4409339c3e1e completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2172894d88190b7b27f78e9fd1521 completed April 17, 2026, 11:19 a.m.
Created at: April 8, 2026, 9:22 p.m.