Triple

T2516899
Position Surface form Disambiguated ID Type / Status
Subject The Meyerowitz Stories E55432 entity
Predicate platform P1292 FINISHED
Object Netflix E118902 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: Netflix | Statement: [The Meyerowitz Stories, platform, Netflix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Netflix
Context triple: [The Meyerowitz Stories, platform, 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. Paramount+
    Paramount+ is a subscription-based streaming service from Paramount Global that offers live sports, original series, and a wide range of on-demand TV shows and movies.
  • 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_69ab49e4749c8190813311efd1630f1b completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd20f8d0c8190bfdcb99a12f59d59 completed March 7, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5cec74ac819093529ce5843ca320 completed March 9, 2026, 11:51 p.m.
Created at: March 6, 2026, 9:46 p.m.