Triple

T10355494
Position Surface form Disambiguated ID Type / Status
Subject The Thin Red Line E243988 entity
Predicate stars P1956 FINISHED
Object George Clooney E11669 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: George Clooney | Statement: [The Thin Red Line, stars, George Clooney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Clooney
Context triple: [The Thin Red Line, stars, George Clooney]
  • A. George Clooney chosen
    George Clooney is an American actor, filmmaker, and activist renowned for his work in film and television as well as his humanitarian and political advocacy.
  • B. Matt Damon
    Matt Damon is an American actor, producer, and screenwriter known for his versatile performances in films such as Good Will Hunting, the Bourne series, and The Martian.
  • C. Tom Hanks
    Tom Hanks is an acclaimed American actor and filmmaker renowned for his versatile performances in films such as "Forrest Gump," "Saving Private Ryan," and "Cast Away."
  • D. Brad Pitt
    Brad Pitt is an American actor and film producer renowned for his leading roles in major Hollywood films and for winning multiple Academy Awards.
  • E. Anthony Howard Goldwyn
    Anthony Howard Goldwyn is an American actor, director, and producer best known for his roles in films like "Ghost" and the TV series "Scandal."
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e953d4888190b7ca0ac932349dbf completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d750a9b4188190a8ecdd9e4d97570b completed April 9, 2026, 7:09 a.m.
Created at: April 6, 2026, 11:58 a.m.