Triple

T2804786
Position Surface form Disambiguated ID Type / Status
Subject Naomi Biden E54025 entity
Predicate hasRelative P367 FINISHED
Object Jill Biden E40024 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: Jill Biden | Statement: [Naomi Biden, hasRelative, Jill Biden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jill Biden
Context triple: [Naomi Biden, hasRelative, Jill Biden]
  • A. Jill Biden chosen
    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.
  • B. Neilia Hunter Biden
    Neilia Hunter Biden was an American educator and the first wife of Joe Biden, who tragically died in a 1972 car accident along with their infant daughter.
  • C. Naomi Biden
    Naomi Biden is an American lawyer and the granddaughter of U.S. President Joe Biden, known for her public presence during his political career and at White House events.
  • D. Melania Trump
    Melania Trump is a Slovenian-American former fashion model who served as First Lady of the United States from 2017 to 2021.
  • E. Michelle Obama
    Michelle Obama is an American lawyer, author, and former First Lady of the United States known for her advocacy on education, health, and military families.
  • 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_69ab49dcee188190b5c6eca9ae9e3469 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde1525888190b3c04e10043c67d6 completed March 7, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69b108c7cfd48190b959e60b9e7fc0fa completed March 11, 2026, 6:16 a.m.
Created at: March 6, 2026, 9:59 p.m.