Triple

T20518152
Position Surface form Disambiguated ID Type / Status
Subject Bibi Besch E503733 entity
Predicate name P16 FINISHED
Object Bibi Besch 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: Bibi Besch | Statement: [Bibi Besch, name, Bibi Besch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bibi Besch
Context triple: [Bibi Besch, name, Bibi Besch]
  • A. Bibi Besch chosen
    Bibi Besch was an Austrian-American actress best known for her film and television work in the 1970s and 1980s, including prominent roles in science fiction and drama.
  • B. Bibi Vogel
    Bibi Vogel was a Brazilian singer and actress best known for her work in popular music and television during the 1960s and 1970s.
  • C. Zita Johann
    Zita Johann was an Austro-Hungarian-born American stage and film actress best known for her role opposite Boris Karloff in the 1932 horror classic "The Mummy."
  • D. Gitta Born
    Gitta Born is a notable member of the Born family, recognized for her association with this prominent lineage.
  • E. Sissy Böhm
    Sissy Böhm is an Austrian actress and writer, known both for her work in film and television and as the daughter of renowned actor Karlheinz Böhm.
  • 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_69e0b4b2aa788190ae9eb37c1d73b1f1 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69f43e0b08190b043f35645b264a0 completed April 20, 2026, 9:48 p.m.
Created at: April 16, 2026, 11:36 a.m.