Triple

T13616807
Position Surface form Disambiguated ID Type / Status
Subject As Good as It Gets E325336 entity
Predicate distributedBy P1951 FINISHED
Object TriStar Pictures E50654 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: TriStar Pictures | Statement: [As Good as It Gets, distributedBy, TriStar Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TriStar Pictures
Context triple: [As Good as It Gets, distributedBy, TriStar Pictures]
  • A. TriStar Pictures chosen
    TriStar Pictures is an American film production and distribution studio known for releasing a wide range of popular Hollywood movies since the 1980s.
  • B. Tri-Star Pictures
    Tri-Star Pictures is an American film production and distribution company known for releasing a wide range of Hollywood movies since the 1980s.
  • C. Buena Vista Pictures
    Buena Vista Pictures was the theatrical distribution arm of The Walt Disney Company, responsible for releasing many of Disney’s live-action and animated films.
  • D. Hollywood Pictures
    Hollywood Pictures was a film production label of The Walt Disney Company that focused on releasing more mature and genre-oriented movies during the 1990s.
  • E. Columbia Pictures
    Columbia Pictures is a historic American film studio that rose to prominence during Hollywood’s Golden Age and became one of the industry’s leading producers and distributors of motion pictures.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0ad0a7c81909c7972187202db96 completed April 12, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78ae7d6908190836172e955b0d7e8 completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:50 p.m.