Triple

T2595767
Position Surface form Disambiguated ID Type / Status
Subject Maye Musk E58226 entity
Predicate givenName P17 FINISHED
Object Maye E58226 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: Maye | Statement: [Maye Musk, givenName, Maye]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maye
Context triple: [Maye Musk, givenName, Maye]
  • A. Maye chosen
    Maye is the first name of Maye Musk, a Canadian-South African model and dietitian known for her long-running fashion career and as the mother of entrepreneur Elon Musk.
  • B. David Lee
    David Lee is an American television producer, director, and writer best known for co-creating the acclaimed sitcoms Frasier and Wings.
  • C. David Lee
    David Lee is a senior Royal Air Force officer who served as Air Officer Commanding-in-Chief of Fighter Command, overseeing the RAF’s fighter aircraft operations.
  • D. Turquoise Erving
    Turquoise Erving is best known as the former wife of legendary American basketball player Julius "Dr. J" Erving.
  • E. Anthony Parker
    Anthony Parker is a former NBA shooting guard who transitioned into basketball operations and now serves as a front-office executive and general manager in the league.
  • 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_69ab4ac14040819098b13f4a27d5c8ff completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd42978f881909f217e7ec9ac3144 completed March 7, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69af83c798088190944e7d754aa9aa06 completed March 10, 2026, 2:36 a.m.
Created at: March 6, 2026, 9:49 p.m.