Triple

T14666155
Position Surface form Disambiguated ID Type / Status
Subject Christoph Sauer E344378 entity
Predicate hasChild P369 FINISHED
Object Christoph Sauer Jr. E344378 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: Christoph Sauer Jr. | Statement: [Christoph Sauer, hasChild, Christoph Sauer Jr.]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christoph Sauer Jr.
Context triple: [Christoph Sauer, hasChild, Christoph Sauer Jr.]
  • A. Christoph Sauer chosen
    Christoph Sauer was an 18th-century German-American printer and publisher known for producing one of the earliest German-language Bibles in North America.
  • B. Stephan Sauer
    Stephan Sauer is a notable individual who shares the surname Sauer and is recognized for achievements significant enough to be specifically referenced.
  • C. Martin Sauer
    Martin Sauer is a relatively common personal name shared by multiple individuals across various professions, including sports, academia, and the arts.
  • D. Christian Brandauer
    Christian Brandauer is the son of Austrian actor and director Klaus Maria Brandauer.
  • E. Markus Sattler
    Markus Sattler is a German software engineer and entrepreneur best known as a co-founder and former CTO of the email marketing platform Mailjet.
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb54c69f8819080a37161deecfba8 completed April 14, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec86ea50c819083d0bbed4c459041 completed May 9, 2026, 5:38 a.m.
Created at: April 10, 2026, 1:27 a.m.