Triple

T13196216
Position Surface form Disambiguated ID Type / Status
Subject Garret Dillahunt E314117 entity
Predicate employer P7 FINISHED
Object Amazon Studios E31212 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: Amazon Studios | Statement: [Garret Dillahunt, employer, Amazon Studios]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazon Studios
Context triple: [Garret Dillahunt, employer, Amazon Studios]
  • A. Amazon Studios chosen
    Amazon Studios is the film and television production and distribution arm of Amazon, known for creating original content for the Prime Video streaming platform.
  • B. Netflix Studios
    Netflix Studios is the in-house production arm of Netflix responsible for developing and producing original films and television series for the streaming platform.
  • C. Annapurna Studios
    Annapurna Studios is a prominent Indian film production and post-production company based in Hyderabad, widely recognized for its role in shaping Telugu cinema.
  • D. ABC studios
    ABC Studios is a television production facility and studio complex associated with the American Broadcasting Company, used for producing and filming various TV shows and game shows.
  • E. Atlas Studios
    Atlas Studios is a major film studio complex in Morocco renowned for its large desert sets and frequent use as a shooting location for international movies and 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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c626058819086f604b11af2d4eb completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f605a48c81909373fcd9dd896b3d completed May 3, 2026, 7:15 a.m.
Created at: April 9, 2026, 9:16 p.m.