Triple

T8430521
Position Surface form Disambiguated ID Type / Status
Subject Barbara Broccoli E199103 entity
Predicate name P16 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: [Barbara Broccoli, name, Barbara Broccoli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barbara Broccoli
Context triple: [Barbara Broccoli, name, 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_69ca8313c99081909a5c6d83b91de5b3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbd1a2efa08190b92c75812003ffdb completed March 31, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce0380ed948190bdba247d67769ade completed April 2, 2026, 5:49 a.m.
Created at: March 30, 2026, 6:07 p.m.