Triple

T18604502
Position Surface form Disambiguated ID Type / Status
Subject Lewis Vernon Harcourt E454703 entity
Predicate alsoKnownAs P39 FINISHED
Object Lulu Harcourt NE NERFINISHED

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: Lulu Harcourt | Statement: [Lewis Vernon Harcourt, alsoKnownAs, Lulu Harcourt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lulu Harcourt
Context triple: [Lewis Vernon Harcourt, alsoKnownAs, Lulu Harcourt]
  • A. Lulu Harcourt chosen
    Lulu Harcourt is the nickname of Lewis Vernon Harcourt, a British Liberal politician who served as Secretary of State for the Colonies in the early 20th century.
  • B. Ella D'Arcy
    Ella D'Arcy was a British fin-de-siècle short story writer associated with literary modernism and the aesthetic movement.
  • C. Lilly Berger
    Lilly Berger is a central teenage protagonist in the coming-of-age drama film "Very Good Girls," navigating first love, friendship, and personal identity.
  • D. Lizzie Brocheré
    Lizzie Brocheré is a French actress known for her work in both European cinema and American television, including a prominent role in the horror anthology series American Horror Story.
  • E. Lola Perrin
    Lola Perrin is a composer and pianist known for her contemporary classical works and collaborations across film, theatre, and interdisciplinary projects.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38bbe7c8190bdec3138e7d413c9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e547535b8c8190ab5a8a92f15f2bcb completed April 19, 2026, 9:21 p.m.
Created at: April 10, 2026, 11:45 a.m.