Triple

T276779
Position Surface form Disambiguated ID Type / Status
Subject Melania Trump E5266 entity
Predicate name P16 FINISHED
Object Melania Trump E5266 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: Melania Trump | Statement: [Melania Trump, name, Melania Trump]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Melania Trump
Context triple: [Melania Trump, name, Melania Trump]
  • A. Melania Trump chosen
    Melania Trump is a Slovenian-American former fashion model who served as First Lady of the United States from 2017 to 2021.
  • B. Jill Biden
    Jill Biden is an American educator and the First Lady of the United States, known for her long career in teaching and her advocacy for military families, community colleges, and cancer research.
  • C. Vanessa Trump
    Vanessa Trump is an American former model and ex-wife of Donald Trump Jr., known for her connection to the Trump family.
  • D. Mary Anne MacLeod Trump
    Mary Anne MacLeod Trump was a Scottish-born American homemaker and philanthropist best known as the mother of Donald Trump and the wife of real estate developer Fred Trump.
  • E. Tiffany Trump
    Tiffany Trump is an American public figure and the younger daughter of former U.S. President Donald Trump, known for her appearances in media and involvement in politics and law.
  • 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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25ded68c88190b1fc595ce329aeb9 completed Feb. 28, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3d4dcaec0819099f5a3721d035cdd completed March 1, 2026, 5:55 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.