Triple

T6823381
Position Surface form Disambiguated ID Type / Status
Subject Hannah Arendt (2012 film) E156953 entity
Predicate hasCastMember P2308 FINISHED
Object Axel Milberg E623345 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: Axel Milberg | Statement: [Hannah Arendt (2012 film), hasCastMember, Axel Milberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Axel Milberg
Context triple: [Hannah Arendt (2012 film), hasCastMember, Axel Milberg]
  • A. Axel Milberg chosen
    Axel Milberg is a German actor known for his extensive work in film and television, including prominent roles in dramas and crime series.
  • B. Carl Molinder
    Carl Molinder is a Swedish film producer best known for his work on the critically acclaimed horror drama "Let the Right One In."
  • C. Hans Axgil
    Hans Axgil is a fictional character in the film "The Danish Girl," portrayed as a compassionate childhood friend and later love interest who supports Lili Elbe through her gender transition.
  • D. Johan Aberg
    Johan Åberg is a Swedish songwriter and producer known for his work on international pop hits, including contributions to artists like Christina Aguilera.
  • E. Charles Boberg
    Charles Boberg is a linguist and scholar of North American English dialects, particularly known for his work on regional variation and phonology.
  • 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_69c688298a288190af3f285d57f76bbe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d580ca448190aa6d52908ca50e39 completed March 27, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7426356a88190a36b53a46c1776e0 completed March 28, 2026, 2:52 a.m.
Created at: March 27, 2026, 2:18 p.m.