Triple

T23002845
Position Surface form Disambiguated ID Type / Status
Subject Ich tu dir weh E572676 entity
Predicate keyboardist P12601 FINISHED
Object Flake Lorenz E1564900 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: Flake Lorenz | Statement: [Ich tu dir weh, keyboardist, Flake Lorenz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flake Lorenz
Context triple: [Ich tu dir weh, keyboardist, Flake Lorenz]
  • A. Flake Lorenz chosen
    Flake Lorenz is a German musician best known as the keyboardist of the industrial metal band Rammstein.
  • B. Christian "Flake" Lorenz
    Christian "Flake" Lorenz is the German keyboardist best known as a founding member of the industrial metal band Rammstein, recognized for his distinctive playing style and eccentric stage presence.
  • C. Florenz
    Florenz was the first name of Florenz Ziegfeld Jr., the influential American Broadway impresario best known for creating the Ziegfeld Follies.
  • D. Leo Farnsworth
    Leo Farnsworth is a wealthy industrialist whose body is inhabited by the soul of a deceased football player in the romantic fantasy comedy film "Heaven Can Wait."
  • E. Frank Faylen
    Frank Faylen was an American character actor best known for his supporting roles in classic films like "It's a Wonderful Life" and "The Lost Weekend," as well as numerous television appearances.
  • 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_69e245b6a3ac81908087599eefe3e365 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f183549bdc81908fdcd44e2c92f7c4 completed April 29, 2026, 4:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c0acabb808190a688aacdf935a9ad completed May 19, 2026, 7:01 a.m.
Created at: April 17, 2026, 3:50 p.m.