Triple

T19578942
Position Surface form Disambiguated ID Type / Status
Subject Klaus Schwarzkopf E489933 entity
Predicate familyName P18 FINISHED
Object Schwarzkopf NE NERFINISHED

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: Schwarzkopf | Statement: [Klaus Schwarzkopf, familyName, Schwarzkopf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwarzkopf
Context triple: [Klaus Schwarzkopf, familyName, Schwarzkopf]
  • A. Schwarzkopf chosen
    Schwarzkopf is a German surname most prominently associated with U.S. Army General Norman Schwarzkopf Jr., who led coalition forces in the Gulf War.
  • B. Schwarzkopf
    Schwarzkopf is a German hair care and styling brand known for its shampoos, dyes, and professional salon products.
  • C. Redken
    Redken is a professional haircare and hair color brand known for its salon-quality products and innovative, science-driven formulas.
  • D. Garnier Fructis
    Garnier Fructis is a popular hair care brand known for its fruit-based formulas and wide range of shampoos, conditioners, and styling products.
  • E. Tresemmé
    Tresemmé is a popular hair care brand known for its salon-inspired shampoos, conditioners, and styling products widely available in retail stores.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8dd9374819098e36349b3211663 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6402693d88190a828c0e136895783 completed April 20, 2026, 3:03 p.m.
Created at: April 10, 2026, 1:42 p.m.