Triple

T9416749
Position Surface form Disambiguated ID Type / Status
Subject Ainsley Whitly E227041 entity
Predicate relative P37 FINISHED
Object Malcolm Bright E630795 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: Malcolm Bright | Statement: [Ainsley Whitly, relative, Malcolm Bright]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malcolm Bright
Context triple: [Ainsley Whitly, relative, Malcolm Bright]
  • A. Malcolm Bright chosen
    Malcolm Bright is a brilliant but psychologically troubled criminal profiler who works with the NYPD to track down serial killers while grappling with the legacy of his own murderous father.
  • B. Malcolm Blight
    Malcolm Blight is a legendary Australian rules footballer and coach, renowned for his brilliant playing career and innovative coaching in the VFL/AFL.
  • C. Malcolm Sinclair
    Malcolm Sinclair is a British actor known for his work in television, film, and theatre, often appearing in character roles in popular UK dramas and comedies.
  • D. Malcolm Weir
    Malcolm Weir is a British scientist and biotechnology entrepreneur best known as the founder of the drug discovery company Heptares Therapeutics.
  • E. Malcolm Dixon
    Malcolm Dixon was a British actor and dwarf performer best known for his roles in fantasy and science-fiction films of the late 20th century.
  • 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_69ca84359e7c819091148ba4b670e436 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd68cb4be08190a47f901a9703f9db completed April 1, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12233f89c8190979d76aee65c0d56 completed April 4, 2026, 2:37 p.m.
Created at: March 30, 2026, 7:48 p.m.