Triple

T10738620
Position Surface form Disambiguated ID Type / Status
Subject Männerpension E253260 entity
Predicate hasCastMember P2308 FINISHED
Object Jochen Nickel E41700 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: Jochen Nickel | Statement: [Männerpension, hasCastMember, Jochen Nickel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jochen Nickel
Context triple: [Männerpension, hasCastMember, Jochen Nickel]
  • A. Jochen Nickel chosen
    Jochen Nickel is a German actor known for his character roles in films and television, including appearances in notable World War II dramas.
  • B. Jochen Kuttler
    Jochen Kuttler is a German local politician who serves as the mayor of the town of Wadern in Saarland.
  • C. Jochen Hecht
    Jochen Hecht is a German former professional ice hockey forward who enjoyed a long NHL career, notably with the Buffalo Sabres, and represented Germany in multiple international tournaments.
  • D. Andreas Scholz
    Andreas Scholz is a person known for bearing the surname Scholz, though no widely recognized public profile or specific notable achievements are clearly associated with him from the given information.
  • E. Hannes Jaenicke
    Hannes Jaenicke is a German actor and documentary filmmaker known for his roles in film and television as well as his environmental activism.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d710424d8c81908ee9b59d622f2af5 completed April 9, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb0a03a1481908edb933b1613a027 completed April 14, 2026, 9:24 p.m.
Created at: April 8, 2026, 9:14 p.m.