Triple

T7047040
Position Surface form Disambiguated ID Type / Status
Subject Lynne Haldeman E163661 entity
Predicate memberOf P10 FINISHED
Object Musk family E156625 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: Musk family | Statement: [Lynne Haldeman, memberOf, Musk family]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Musk family
Context triple: [Lynne Haldeman, memberOf, Musk family]
  • A. Errol Musk
    Errol Musk is a South African electromechanical engineer, pilot, and property developer best known as the controversial father of entrepreneur Elon Musk.
  • B. Maye Musk
    Maye Musk is a Canadian-South African model and dietitian who has had a decades-long international modeling career and is the mother of entrepreneur Elon Musk.
  • C. Tosca Musk
    Tosca Musk is a South African–Canadian filmmaker and producer, best known as the co-founder and CEO of the romance-focused streaming platform Passionflix.
  • D. Zuckerberg family
    The Zuckerberg family is the American family of Meta Platforms co-founder Mark Zuckerberg, known for its significant influence in technology and large-scale philanthropic efforts.
  • E. Musk chosen
    Musk is a prominent surname most widely associated with entrepreneur Elon Musk and his family, including businessman and restaurateur Kimbal Musk.
  • 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_69c6885f598c8190b6b6495c59d8d962 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e23a72f481909ce77ef73b06ea95 completed March 27, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7887e6e50819088c23c9b45861a54 completed March 28, 2026, 7:51 a.m.
Created at: March 27, 2026, 2:37 p.m.