Triple

T21632921
Position Surface form Disambiguated ID Type / Status
Subject The Smurfs (2011 film) E533878 entity
Predicate stars P1956 FINISHED
Object Hank Azaria 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: Hank Azaria | Statement: [The Smurfs (2011 film), stars, Hank Azaria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hank Azaria
Context triple: [The Smurfs (2011 film), stars, Hank Azaria]
  • A. Hank Azaria chosen
    Hank Azaria is an American actor, comedian, and voice artist best known for voicing numerous characters on the animated television series "The Simpsons."
  • B. Will Murray
    Will Murray is an American writer best known for his extensive work continuing classic pulp fiction series, particularly the Doc Savage novels.
  • C. Richard Schaal
    Richard Schaal was an American character actor known for his work in television comedies such as "The Mary Tyler Moore Show" and "The Dick Van Dyke Show."
  • D. Michael Ian Black
    Michael Ian Black is an American comedian, actor, writer, and director known for his work on "The State," "Stella," and numerous stand-up and television appearances.
  • E. Tony Hale
    Tony Hale is an American actor and comedian best known for his Emmy-winning roles in the television series "Arrested Development" and "Veep."
  • 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_69e0c465ae7481908577b7209fdb2a77 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef52185dbc819096ad2fc5b7d953f8 completed April 27, 2026, 12:10 p.m.
Created at: April 16, 2026, 6:35 p.m.