Triple

T12088030
Position Surface form Disambiguated ID Type / Status
Subject Fanny Einstein E287860 entity
Predicate marriedName P18 FINISHED
Object Fanny Einstein E287860 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: Fanny Einstein | Statement: [Fanny Einstein, marriedName, Fanny Einstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fanny Einstein
Context triple: [Fanny Einstein, marriedName, Fanny Einstein]
  • A. Fanny Einstein chosen
    Fanny Einstein was a woman known primarily through historical records under her married name, originally born as Fanny Koch.
  • B. Evelyn Einstein
    Evelyn Einstein was the adopted granddaughter of physicist Albert Einstein, known for her later-life legal disputes over the use of the Einstein name and image.
  • C. Felice Frankel
    Felice Frankel is a renowned science photographer and research scientist known for her striking visualizations that communicate complex scientific concepts to broad audiences.
  • D. Beatrice Kaufman
    Beatrice Kaufman was an American writer, editor, and prominent New York literary hostess known for her sharp wit and influential salon, and as the wife of playwright George S. Kaufman.
  • E. Franny
    Franny is a common diminutive or nickname for the given name Frances.
  • 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_69d6ab4964708190850585628b287b0c completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d91514c78c8190bc1cd569e524e8b4 completed April 10, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f668eff88190877ce9bb991c1258 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:48 p.m.