Triple

T2200694
Position Surface form Disambiguated ID Type / Status
Subject The Fate of the Furious E50480 entity
Predicate editedBy P1954 FINISHED
Object Christian Wagner E197182 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: Christian Wagner | Statement: [The Fate of the Furious, editedBy, Christian Wagner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christian Wagner
Context triple: [The Fate of the Furious, editedBy, Christian Wagner]
  • A. Christian Wagner chosen
    Christian Wagner is a film editor known for his work on major Hollywood productions, including the superhero film "The Suicide Squad."
  • B. Nal Kalchbrenner
    Nal Kalchbrenner is a computer scientist and machine learning researcher known for co-developing WaveNet, a groundbreaking deep generative model for raw audio.
  • C. Alberich Zwyssig
    Alberich Zwyssig was a Swiss monk and composer best known for writing the music to the Swiss national anthem, the "Swiss Psalm."
  • D. Reinhard
    Reinhard is a masculine German given name historically borne by several notable figures, including high-ranking officials in Nazi Germany.
  • E. Ludwig Crüwell
    Ludwig Crüwell was a German Wehrmacht general and Afrika Korps commander during World War II, noted for his leadership in the North African campaign.
  • 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_69a88b044ab48190add007487680f009 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abbfa06bb4819092d7021358846e5f completed March 7, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5dbb6e8481908610337cfd2a4bd1 completed March 9, 2026, 5:42 a.m.
Created at: March 4, 2026, 7:46 p.m.