Triple

T6268600
Position Surface form Disambiguated ID Type / Status
Subject Mick Jagger E140473 entity
Predicate hasChild P369 FINISHED
Object James Jagger E331286 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: James Jagger | Statement: [Mick Jagger, hasChild, James Jagger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: James Jagger
Context triple: [Mick Jagger, hasChild, James Jagger]
  • A. James Jagger chosen
    James Jagger is a British actor and musician, best known as the son of Mick Jagger and Jerry Hall and for roles in projects like the TV series "Vinyl."
  • B. Pip Torrens
    Pip Torrens is a British actor known for his character roles in film and television, including appearances in series such as "Patrick Melrose," "The Crown," and "Preacher."
  • C. John Brierley
    John Brierley is the real-life Australian man whose childhood journey from India to adoption and later search for his birth family inspired the book and film "Lion."
  • D. Gabriel Jagger
    Gabriel Jagger is a British model and media figure, best known as one of Mick Jagger and Jerry Hall’s children.
  • E. Jonathan Hyde
    Jonathan Hyde is an English-Australian actor known for his roles in films like "Titanic," "Jumanji," and "The Mummy," as well as extensive work in television, theatre, and voice acting.
  • 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_69c008cabc4081909723e2547c9d6cc0 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063a28da081909f4bec8f7c1dedef completed March 22, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c24460f1bc8190b15ca58331410ec2 completed March 24, 2026, 7:59 a.m.
Created at: March 22, 2026, 4:25 p.m.