Triple

T4101100
Position Surface form Disambiguated ID Type / Status
Subject Mudbound E87941 entity
Predicate starring P1507 FINISHED
Object Jason Mitchell E233166 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: Jason Mitchell | Statement: [Mudbound, starring, Jason Mitchell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jason Mitchell
Context triple: [Mudbound, starring, Jason Mitchell]
  • A. Jason Mitchell chosen
    Jason Mitchell is an American actor known for his breakout role as Eazy-E in "Straight Outta Compton" and appearances in films such as "Mudbound" and "Kong: Skull Island."
  • B. Michael Ealy
    Michael Ealy is an American actor known for his roles in films like "Barbershop," "Think Like a Man," and "2 Fast 2 Furious," as well as various television series.
  • C. Eriq La Salle
    Eriq La Salle is an American actor, director, and producer best known for his role as Dr. Peter Benton on the television series "ER."
  • D. Michael Pennington
    Michael Pennington is a distinguished English actor and director, particularly renowned for his work in classical theatre and Shakespearean performance.
  • E. Luke Goss
    Luke Goss is an English actor and former drummer best known for his roles in genre films such as "Blade II" and "Hellboy II: The Golden Army."
  • 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_69aed94564cc8190a9c1457daedb6e7f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefd0ed168819093c83ba079d6725c completed March 9, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b7833b081909bf5a87ee709b49f completed March 14, 2026, 2:06 p.m.
Created at: March 9, 2026, 3:40 p.m.