Triple

T22454229
Position Surface form Disambiguated ID Type / Status
Subject Toni Trucks E555070 entity
Predicate notableWork P4 FINISHED
Object Grimm 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: Grimm | Statement: [Toni Trucks, notableWork, Grimm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grimm
Context triple: [Toni Trucks, notableWork, Grimm]
  • A. Grimm chosen
    Grimm is a dark fantasy police procedural television series that blends crime-solving with folklore-inspired supernatural elements.
  • B. Grimm
    Grimm is a German surname most famously associated with the Brothers Grimm, Jacob and Wilhelm, renowned for their collection of folk and fairy tales.
  • C. Grimm’s Enchanted Forest
    Grimm’s Enchanted Forest is a fairy-tale themed area in Europa-Park that immerses visitors in scenes and characters from the classic Brothers Grimm stories.
  • D. Company of Wolves
    Company of Wolves is a film production company known for its involvement in British cinema projects such as the 2002 adaptation of "Nicholas Nickleby."
  • E. The Wolves of Mercy Falls
    The Wolves of Mercy Falls is a young adult paranormal romance series by Maggie Stiefvater that follows the intense, bittersweet relationship between a girl and a boy who transforms into a wolf with the changing seasons.
  • 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_69e11e5113208190ab58c6b595f9d1d0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b4e2bd4819083e5bed44e9776c6 completed April 29, 2026, 1:13 a.m.
Created at: April 16, 2026, 8:48 p.m.