Triple

T22141610
Position Surface form Disambiguated ID Type / Status
Subject Biggie: I Got a Story to Tell E547171 entity
Predicate publisher P29 FINISHED
Object Netflix 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: Netflix | Statement: [Biggie: I Got a Story to Tell, publisher, Netflix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Netflix
Context triple: [Biggie: I Got a Story to Tell, publisher, Netflix]
  • A. Netflix chosen
    Netflix is a global streaming entertainment company best known for its vast library of films and TV series and its influential original content.
  • B. Hulu
    Hulu is a U.S.-based subscription streaming service offering on-demand access to a wide range of television shows, films, and original content.
  • C. Amazon Prime Video
    Amazon Prime Video is a subscription-based streaming service from Amazon that offers a wide range of movies, TV series, and original content available on-demand across multiple devices.
  • D. HBO Max
    HBO Max is a streaming service from WarnerMedia that offers a wide library of movies, series, and original content from HBO and related brands.
  • E. Amazon Freevee
    Amazon Freevee is a free, ad-supported streaming service from Amazon that offers a mix of movies, TV shows, and original programming.
  • 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_69e11e3a95d88190a3bd80d9471976c3 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129beb6c8819083be3b7479bc032f completed April 28, 2026, 9:42 p.m.
Created at: April 16, 2026, 8:32 p.m.