Triple

T18204585
Position Surface form Disambiguated ID Type / Status
Subject ViT E435871 entity
Predicate introducedBy P513 FINISHED
Object Thomas Unterthiner 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: Thomas Unterthiner | Statement: [ViT, introducedBy, Thomas Unterthiner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomas Unterthiner
Context triple: [ViT, introducedBy, Thomas Unterthiner]
  • A. Thomas Unterthiner chosen
    Thomas Unterthiner is a machine learning researcher known for co-introducing the Fréchet Inception Distance (FID), a widely used metric for evaluating generative models.
  • B. Patrick Wachsberger
    Patrick Wachsberger is a French film producer and studio executive best known for co-founding Summit Entertainment and overseeing major franchises such as the Twilight series.
  • C. Joseph Sonnleithner
    Joseph Sonnleithner was an Austrian librettist, lawyer, and cultural figure best known for writing the original libretto for Beethoven’s opera "Fidelio."
  • D. John Hofer
    John Hofer is a musician best known as a member of the rock band Rogue Wave.
  • E. Bill Steinkellner
    Bill Steinkellner is an American television writer and producer best known for his work on popular sitcoms, often in collaboration with his wife Cheri Steinkellner.
  • 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_69d8b90dba6481908e119eb9aa4ca0cb completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e222831081908f7d5500424e3acb completed April 19, 2026, 2:09 p.m.
Created at: April 10, 2026, 10:32 a.m.