Triple

T9283967
Position Surface form Disambiguated ID Type / Status
Subject The Lost Honour of Katharina Blum E223138 entity
Predicate mainCharacter P1183 FINISHED
Object Katharina Blum E623375 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: Katharina Blum | Statement: [The Lost Honour of Katharina Blum, mainCharacter, Katharina Blum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katharina Blum
Context triple: [The Lost Honour of Katharina Blum, mainCharacter, Katharina Blum]
  • A. Ulrike Körner
    Ulrike Körner is a person notable enough to be recognized as a prominent bearer of the surname Körner.
  • B. Gudrun Landgrebe chosen
    Gudrun Landgrebe is a German actress known for her work in film and television since the 1980s, including prominent roles in dramas and literary adaptations.
  • C. Ursula Steinhoff
    Ursula Steinhoff was the wife of German Luftwaffe ace and postwar Bundeswehr general Johannes Steinhoff.
  • D. Liesbeth Spies
    Liesbeth Spies is a Dutch politician of the Christian Democratic Appeal (CDA) who has served in roles including Minister of the Interior and Kingdom Relations and mayor of Alphen aan den Rijn.
  • E. Rose Stradner
    Rose Stradner was an Austrian-American actress known for her work in Hollywood films of the 1930s and 1940s.
  • 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_69ca842123588190b3f2e1a69037d141 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd081e72988190917f425e64631837 completed April 1, 2026, 11:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0b21d8f1081909b2493151fde4a5f completed April 4, 2026, 6:39 a.m.
Created at: March 30, 2026, 7:34 p.m.