Triple

T14874830
Position Surface form Disambiguated ID Type / Status
Subject Movies! E349838 entity
Predicate hasAlternativeName P39 FINISHED
Object Movies! Network E349838 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: Movies! Network | Statement: [Movies!, hasAlternativeName, Movies! Network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Movies! Network
Context triple: [Movies!, hasAlternativeName, Movies! Network]
  • A. Movies! (TV network) chosen
    Movies! is an American digital multicast television network specializing in airing a wide range of classic and contemporary feature films.
  • B. The Movie Network
    The Movie Network was a Canadian premium television service known for broadcasting commercial-free movies, original series, and special event programming.
  • C. Flix
    Flix is a small municipality in Catalonia, Spain, known for its location along a bend of the Ebro River and its historical industrial and hydroelectric activities.
  • D. Flix
    Flix is one of the official cartoon mascots created to represent and promote the UEFA Euro 2008 football championship.
  • E. Are Media
    Are Media is a major Australian magazine and digital media company that publishes a wide range of lifestyle, fashion, and entertainment titles.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e3e5d48190a132f2cf012b01e2 completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b52c12481908d0173a2a3ed854b completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 1:55 a.m.