Triple

T708200
Position Surface form Disambiguated ID Type / Status
Subject Donald Trump E14147 entity
Predicate spouse P13 FINISHED
Object Marla Maples E34532 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: Marla Maples | Statement: [Donald Trump, spouse, Marla Maples]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marla Maples
Context triple: [Donald Trump, spouse, Marla Maples]
  • A. Marla Maples chosen
    Marla Maples is an American actress and television personality best known for her high-profile marriage to businessman and future U.S. President Donald Trump in the 1990s.
  • B. Elaine Mason
    Elaine Mason was a British nurse who became the second wife of theoretical physicist Stephen Hawking.
  • C. Melinda Rogers
    Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
  • D. Margo Wilson
    Margo Wilson was a pioneering Canadian evolutionary psychologist best known for her influential research on violence, homicide, and parental investment, often conducted in collaboration with Martin Daly.
  • E. Margo Anderson
    Margo Anderson is best known as a former wife of American country music star Kenny Rogers.
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a548e6dc819090d31ce33493a396 completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad089201a08190a84c7d8f32238297 completed March 8, 2026, 5:26 a.m.
Created at: March 1, 2026, 7:36 p.m.