Triple

T1618452
Position Surface form Disambiguated ID Type / Status
Subject Felicia Schiff Warburg E34774 entity
Predicate memberOf P10 FINISHED
Object Warburg family E120866 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: Warburg family | Statement: [Felicia Schiff Warburg, memberOf, Warburg family]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warburg family
Context triple: [Felicia Schiff Warburg, memberOf, Warburg family]
  • A. Warburg family chosen
    The Warburg family is a prominent German-Jewish banking and philanthropic dynasty influential in international finance, culture, and public life from the 19th century onward.
  • B. Krupp family
    The Krupp family is a prominent German industrial dynasty historically known for its powerful steel and armaments empire centered in Essen.
  • C. Neustadt family
    The Neustadt family is a philanthropic family known for endowing and supporting the prestigious Neustadt International Prize for Literature.
  • D. Thyssen-Bornemisza family
    The Thyssen-Bornemisza family is a wealthy European industrial and aristocratic dynasty renowned for assembling one of the world’s most significant private art collections.
  • E. Gütermann family
    The Gütermann family is a notable German industrial family best known for its long-standing involvement in the textile and thread manufacturing industry.
  • 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_69a885ffc5ec819091afa325d5f9611c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909addb348190a80a97422efcaa63 completed March 5, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad51cf7b7c8190847ab6795fb5613b completed March 8, 2026, 10:39 a.m.
Created at: March 4, 2026, 7:28 p.m.