Triple

T13702253
Position Surface form Disambiguated ID Type / Status
Subject The Counselor E328548 entity
Predicate stars P1956 FINISHED
Object Bruno Ganz E116125 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: Bruno Ganz | Statement: [The Counselor, stars, Bruno Ganz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bruno Ganz
Context triple: [The Counselor, stars, Bruno Ganz]
  • A. Bruno Ganz chosen
    Bruno Ganz was a renowned Swiss actor acclaimed for his intense and nuanced performances in European cinema, particularly in films like "Wings of Desire" and "Downfall."
  • B. Jürgen Menzel
    Jürgen Menzel is a person notable enough to be recognized as a significant bearer of the surname Menzel.
  • C. Klaus Maria Brandauer
    Klaus Maria Brandauer is an acclaimed Austrian actor and director known internationally for his intense, charismatic performances in films such as "Out of Africa" and "Mephisto."
  • D. Klaus Menzel
    Klaus Menzel is a notable individual who shares the surname Menzel, recognized enough to be specifically distinguished among bearers of the name.
  • E. Armin Mueller-Stahl
    Armin Mueller-Stahl is a German actor and former East German film star known internationally for his versatile performances in both European cinema and Hollywood films.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dcad162158819089280ee1e6b5c2cf completed April 13, 2026, 8:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69f794575d3881908de6ed988d848918 completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:54 p.m.