Triple

T10935501
Position Surface form Disambiguated ID Type / Status
Subject Monarch E258321 entity
Predicate notableMember P10 FINISHED
Object Vivienne Graham E792809 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: Vivienne Graham | Statement: [Monarch, notableMember, Vivienne Graham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vivienne Graham
Context triple: [Monarch, notableMember, Vivienne Graham]
  • A. Vivienne Graham chosen
    Vivienne Graham is a Monarch scientist in the MonsterVerse franchise who specializes in studying giant monsters like Godzilla.
  • B. Vivienne Faull
    Vivienne Faull is a senior Church of England bishop who has held prominent leadership roles, including serving as the diocesan bishop in Bristol.
  • C. Vivienne Eytle
    Vivienne Eytle is an actress known for her role in the television film "The Josephine Baker Story."
  • D. Vivienne Haigh-Wood
    Vivienne Haigh-Wood was an English governess and writer best known as the first wife of poet T. S. Eliot and for her troubled marriage that significantly influenced his life and work.
  • E. Mary Garrard
    Mary Garrard is an American art historian and feminist scholar best known for her influential work on women artists such as Artemisia Gentileschi and for advancing feminist perspectives in art history.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770aee178819082c1671a37ff7d82 completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23bee9b208190aee8f938dff3f234 completed April 17, 2026, 1:55 p.m.
Created at: April 8, 2026, 9:23 p.m.