Triple

T12620601
Position Surface form Disambiguated ID Type / Status
Subject Frank E301367 entity
Predicate hasVariant P455 FINISHED
Object Franke E745431 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: Franke | Statement: [Frank, hasVariant, Franke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Franke
Context triple: [Frank, hasVariant, Franke]
  • A. Franke chosen
    Franke is a variant form of the given name Frank, typically used as a surname or less common personal name in Germanic-speaking regions.
  • B. Blomberg
    Blomberg is a small town in the Lippe district of North Rhine-Westphalia, Germany, known as the birthplace of former German chancellor Gerhard Schröder.
  • C. Duravit
    Duravit is a German manufacturer renowned for its high-quality, design-focused bathroom ceramics and furnishings, often created in collaboration with leading designers.
  • D. Petit & Fritsen
    Petit & Fritsen is a historic Dutch bell foundry renowned for casting church bells and carillons used in notable towers and monuments worldwide.
  • E. Gaggenau
    Gaggenau is a town in the state of Baden-Württemberg in southwestern Germany, located in the Murg Valley near the Black Forest.
  • 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_69d7bdeaf49c8190b13800111fa77ea3 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d960c75c9c819092265ebc2b39f21d completed April 10, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ed6f79881908872c644a9789f04 completed May 2, 2026, 8:30 p.m.
Created at: April 9, 2026, 5:13 p.m.