Triple

T18240600
Position Surface form Disambiguated ID Type / Status
Subject Ride (2014 film) E436797 entity
Predicate starring P1507 FINISHED
Object Richard Kind 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: Richard Kind | Statement: [Ride (2014 film), starring, Richard Kind]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Richard Kind
Context triple: [Ride (2014 film), starring, Richard Kind]
  • A. Richard Kind chosen
    Richard Kind is an American character actor known for his comedic roles in television and film, including extensive voice work in animated movies.
  • B. Michael Klingensmith
    Michael Klingensmith is an American media executive best known for helping launch and lead major magazine brands, including playing a key role in the creation of Entertainment Weekly.
  • C. Charlie Fink
    Charlie Fink is a British singer-songwriter, producer, and filmmaker best known as the frontman and primary songwriter of the indie folk band Noah and the Whale.
  • D. Michael Daves
    Michael Daves is an American bluegrass and roots musician known for his high-energy vocal style and collaborations with prominent artists such as mandolinist Chris Thile.
  • E. Ken Kaufman
    Ken Kaufman is an American screenwriter known for his work on major studio films, including the Western thriller "The Missing."
  • 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_69d8b91104e08190a8241f7d260a5162 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4f7e287548190b666a990e5b168b0 completed April 19, 2026, 3:42 p.m.
Created at: April 10, 2026, 10:33 a.m.