Triple

T5055640
Position Surface form Disambiguated ID Type / Status
Subject GoldenEye E113895 entity
Predicate producer P490 FINISHED
Object Barbara Broccoli E199103 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: Barbara Broccoli | Statement: [GoldenEye, producer, Barbara Broccoli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barbara Broccoli
Context triple: [GoldenEye, producer, Barbara Broccoli]
  • A. Barbara Broccoli chosen
    Barbara Broccoli is a prominent film producer best known for overseeing the James Bond franchise through Eon Productions.
  • B. Kate O'Mara
    Kate O'Mara was a British actress best known for her glamorous, often villainous roles in television dramas such as Dynasty and Doctor Who.
  • C. Vikki Heywood
    Vikki Heywood is a British arts executive best known for her leadership roles in major cultural institutions, including serving as executive director of the Royal Shakespeare Company.
  • D. Catherine McGoohan
    Catherine McGoohan is an actress and producer, known for her work in film and television and as the daughter of acclaimed actor Patrick McGoohan.
  • E. Claire Bloom
    Claire Bloom is an acclaimed English actress known for her distinguished stage and screen career, including prominent roles in classic films, television dramas, and Shakespearean productions.
  • 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_69bd443aa1f88190abb992d138f2cf42 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd744e45588190beaa2f96bb2f41e2 completed March 20, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea489eb4c8190ad3a5480b909ef70 completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:38 p.m.