Triple

T19255490
Position Surface form Disambiguated ID Type / Status
Subject George E481505 entity
Predicate hasFeminineForm P1613 FINISHED
Object Georgette 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: Georgette | Statement: [George, hasFeminineForm, Georgette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Georgette
Context triple: [George, hasFeminineForm, Georgette]
  • A. Georgette chosen
    Georgette is the given name of British actress Googie Withers, who was born Georgette Lizette Withers.
  • B. Georgette
    Georgette is a central, tragic transgender character in Hubert Selby Jr.’s novel "Last Exit to Brooklyn," whose life reflects the book’s themes of marginalization and brutality.
  • C. Georgette
    Georgette is a comic servant character in Molière’s play "L’École des femmes," known for her earthy wit and role in highlighting the play’s social and gender tensions.
  • D. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • E. Louise
    Louise is an opera by French composer Gustave Charpentier, renowned for its realistic portrayal of Parisian working-class life and its influential role in early 20th-century French opera.
  • 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_69d8e8cd9d1081908a181d02b88b59b8 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fb3459d08190a7c28ed3f8c82a97 completed April 20, 2026, 10:08 a.m.
Created at: April 10, 2026, 1:28 p.m.