Triple

T10349461
Position Surface form Disambiguated ID Type / Status
Subject Lula Rose Gardner E243840 entity
Predicate father P120 FINISHED
Object Dave Gardner E852832 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: Dave Gardner | Statement: [Lula Rose Gardner, father, Dave Gardner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dave Gardner
Context triple: [Lula Rose Gardner, father, Dave Gardner]
  • A. Dave Gardner
    Dave Gardner is a British sports agent and businessman known for his high-profile connections in the football world and relationships with celebrities.
  • B. Dave Gardner chosen
    Dave Gardner is the son of Sailor Gene Gardner and a member of the Gardner family.
  • C. Tim Gardner
    Tim Gardner is a neuroscientist and entrepreneur known for co-founding Neuralink, a company developing advanced brain–computer interface technology.
  • D. Jimmy Gardner
    Jimmy Gardner was an early 20th-century Canadian ice hockey player, coach, and executive who played a key role in organizing professional hockey and shaping the sport’s development in North America.
  • E. Mark Gardner
    Mark Gardner is a name shared by several notable individuals, including a former Major League Baseball pitcher and a professional ice hockey coach.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e946cbb881909b88536d0107995d completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7508e325c8190a88c2b972f8a6846 completed April 9, 2026, 7:09 a.m.
Created at: April 6, 2026, 11:57 a.m.