Triple

T8450729
Position Surface form Disambiguated ID Type / Status
Subject The Big Short E199791 entity
Predicate castMember P1668 FINISHED
Object Max Greenfield E77663 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: Max Greenfield | Statement: [The Big Short, castMember, Max Greenfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Max Greenfield
Context triple: [The Big Short, castMember, Max Greenfield]
  • A. Max Greenfield chosen
    Max Greenfield is an American actor best known for his role as Schmidt on the television sitcom "New Girl."
  • B. Caleb McLaughlin
    Caleb McLaughlin is an American actor best known for playing Lucas Sinclair in the Netflix science-fiction horror series "Stranger Things."
  • C. Adam Kimmel
    Adam Kimmel is an American cinematographer known for his work on acclaimed films such as "Capote," "Lars and the Real Girl," and "Never Let Me Go."
  • D. Noah Centineo
    Noah Centineo is an American actor known for his breakout roles in teen romantic comedies like Netflix’s "To All the Boys I’ve Loved Before" series and for expanding into superhero films and action projects.
  • E. Logan Marshall-Green
    Logan Marshall-Green is an American actor and director known for his roles in films like "Prometheus" and "Upgrade" as well as various television series.
  • 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_69ca8318231881908fd1bc1c4d45d286 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe44815488190a912d63512e19af0 completed March 31, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4dc984ec8190910e25f36d538928 completed April 2, 2026, 11:06 a.m.
Created at: March 30, 2026, 6:09 p.m.