Triple

T405885
Position Surface form Disambiguated ID Type / Status
Subject Maye Musk E9381 entity
Predicate hasSibling P363 FINISHED
Object Wendy Haldeman E163661 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: Wendy Haldeman | Statement: [Maye Musk, hasSibling, Wendy Haldeman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wendy Haldeman
Context triple: [Maye Musk, hasSibling, Wendy Haldeman]
  • A. Lynne Haldeman chosen
    Lynne Haldeman is a member of the Musk family and the sister of model and dietitian Maye Musk, making her an aunt of entrepreneur Elon Musk.
  • B. Maye Haldeman
    Maye Haldeman is a Canadian-South African model and dietitian best known as Maye Musk, the mother of entrepreneur Elon Musk and a prominent figure in fashion and nutrition.
  • C. Adrienne Nesser
    Adrienne Nesser is an American activist and former boutique owner best known as the longtime wife of Green Day frontman Billie Joe Armstrong.
  • D. Karen Verne
    Karen Verne was a German-born actress who appeared in Hollywood films of the 1940s and was once married to actor Peter Lorre.
  • E. Alanna Heiss
    Alanna Heiss is an American curator and arts administrator best known for pioneering alternative art spaces and founding the influential contemporary art institution MoMA PS1 in New York City.
  • 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_69a2e8004cb88190b92ed1add6abf41a completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ecbc00508190bbb602179273f29c completed Feb. 28, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad089201a08190a84c7d8f32238297 completed March 8, 2026, 5:26 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.