Triple

T752336
Position Surface form Disambiguated ID Type / Status
Subject Franziska Boas E15476 entity
Predicate givenName P17 FINISHED
Object Franziska E83113 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: Franziska | Statement: [Franziska Boas, givenName, Franziska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Franziska
Context triple: [Franziska Boas, givenName, Franziska]
  • A. Franziska chosen
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • B. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • C. Bettina
    Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
  • D. Dorothee
    Dorothee is a feminine given name, commonly used in German- and French-speaking countries, that is a variant of the name Dorothea.
  • E. Fanny Koch
    Fanny Koch was the mother of Elsa Einstein, making her the maternal grandmother of physicist Albert Einstein.
  • 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_69a493599a0081908da65f3407af1ef2 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a64d7d2c8190a6059adcb8fbd34f completed March 1, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c009d5048190b2a137b6ed8b60ec completed March 4, 2026, 5:15 a.m.
Created at: March 1, 2026, 7:37 p.m.