Triple

T6460070
Position Surface form Disambiguated ID Type / Status
Subject The Economist Innovation Award E142094 entity
Predicate notableRecipient P108 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 Economist Innovation Award, notableRecipient, Netflix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Netflix
Context triple: [The Economist Innovation Award, notableRecipient, 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 (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_69c008d2f91c8190a8178767a35e08fc completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c069f50ea88190af29c8c249ff2b69 completed March 22, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64be1fad88190af07b7053811e3f2 completed March 27, 2026, 9:20 a.m.
Created at: March 22, 2026, 4:48 p.m.