Triple

T13607587
Position Surface form Disambiguated ID Type / Status
Subject Barber E325104 entity
Predicate hasNotableBearer P458 FINISHED
Object Lynn Barber E866267 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: Lynn Barber | Statement: [Barber, hasNotableBearer, Lynn Barber]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lynn Barber
Context triple: [Barber, hasNotableBearer, Lynn Barber]
  • A. Lynn Barber chosen
    Lynn Barber is a British journalist and memoirist whose autobiographical writings, including the memoir that inspired the film "An Education," are known for their candor and sharp insight.
  • B. Rosemary Leith
    Rosemary Leith is a Canadian-born entrepreneur and internet governance leader who co-founded the World Wide Web Foundation and serves on various boards related to technology and public policy.
  • C. Lynn Carlin
    Lynn Carlin is an American actress best known for her Oscar-nominated film debut in John Cassavetes' 1968 drama "Faces."
  • D. Tina Lifford
    Tina Lifford is an American actress best known for her roles in film and television, including her acclaimed performance as Violet Bordelon on the drama series "Queen Sugar."
  • E. Joan Bakewell
    Joan Bakewell is a British journalist, broadcaster, and writer renowned for her long career in television and radio and her influential commentary on culture and public affairs.
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb07f462c8190b5b5e115d550037f completed April 12, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f96280881908bab3af5c80f6d55 completed May 3, 2026, 5:02 p.m.
Created at: April 9, 2026, 9:50 p.m.