Triple

T19681395
Position Surface form Disambiguated ID Type / Status
Subject Georgina E472597 entity
Predicate sharesRootWith P3438 FINISHED
Object Georgine 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: Georgine | Statement: [Georgina, sharesRootWith, Georgine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Georgine
Context triple: [Georgina, sharesRootWith, Georgine]
  • A. Georgina chosen
    Georgina is a feminine given name used in various English-speaking and European countries, often considered a variant of Georgia or the feminine form of George.
  • B. Georgina
    Georgina is a lakeside town in Ontario, Canada, known for its recreational waterfront communities and proximity to Lake Simcoe.
  • 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. Georgette
    Georgette is the given name of British actress Googie Withers, who was born Georgette Lizette Withers.
  • E. 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.
  • 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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e641bf97348190bc31b00ed4ec6cad completed April 20, 2026, 3:09 p.m.
Created at: April 10, 2026, 1:45 p.m.