Triple

T5143871
Position Surface form Disambiguated ID Type / Status
Subject Love, Antosha E116021 entity
Predicate subjectOfFilm P22751 FINISHED
Object Anton Yelchin E3122 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: Anton Yelchin | Statement: [Love, Antosha, subjectOfFilm, Anton Yelchin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anton Yelchin
Context triple: [Love, Antosha, subjectOfFilm, Anton Yelchin]
  • A. Anton Yelchin chosen
    Anton Yelchin was a Russian-American actor best known for playing Pavel Chekov in the rebooted Star Trek film series and for his acclaimed performances in independent movies before his untimely death in 2016.
  • B. Viktor Yelchin
    Viktor Yelchin is best known as the father of the late actor Anton Yelchin, who gained fame for his roles in films such as the rebooted Star Trek series.
  • C. Ethan Embry
    Ethan Embry is an American actor known for his roles in 1990s films such as "Empire Records," "Can't Hardly Wait," and various television series.
  • D. Garrett Hedlund
    Garrett Hedlund is an American actor and singer known for roles in films such as "Tron: Legacy," "Friday Night Lights," and "Country Strong."
  • E. Dylan O'Brien
    Dylan O'Brien is an American actor best known for starring in the "Maze Runner" film series and the TV show "Teen Wolf."
  • 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_69bd4446c0e08190a7c29dc74976bf03 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7883004881909c763da818d9b6e2 completed March 20, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefa31458819094b53cbc7a2f5677 completed March 21, 2026, 7:21 p.m.
Created at: March 20, 2026, 1:43 p.m.