Triple

T3595494
Position Surface form Disambiguated ID Type / Status
Subject Rudolf Virchow E76129 entity
Predicate spouse P13 FINISHED
Object Rose Mayer E76129 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: Rose Mayer | Statement: [Rudolf Virchow, spouse, Rose Mayer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rose Mayer
Context triple: [Rudolf Virchow, spouse, Rose Mayer]
  • A. Rose Mayer chosen
    Rose Mayer was the wife of influential German physician and pathologist Rudolf Virchow, a key figure in 19th-century medical and scientific circles.
  • B. Catherine Bauer Wurster
    Catherine Bauer Wurster was a pioneering American housing policy expert and reformer who helped shape modern public housing and urban planning in the United States.
  • C. Mary Costa
    Mary Costa is an American operatic soprano and actress best known for providing the voice of Princess Aurora in Disney's animated film "Sleeping Beauty."
  • D. Nancy Schön
    Nancy Schön is an American sculptor best known for her beloved public bronze sculptures, including the iconic "Make Way for Ducklings" installation in Boston.
  • E. Rosemarie DeWitt
    Rosemarie DeWitt is an American actress known for her work in film and television, including prominent roles in projects like "Rachel Getting Married," "United States of Tara," and "La La Land."
  • 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_69ad85d8042081908af94a04c410dec0 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc15f41cc819085b3e897d823757d completed March 8, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b403130cf081909bb90800d7dc2d6f completed March 13, 2026, 12:29 p.m.
Created at: March 8, 2026, 3:22 p.m.