Triple

T16994450
Position Surface form Disambiguated ID Type / Status
Subject Fox Movies E412276 entity
Predicate hasBrand P1500 FINISHED
Object Fox Movies E412276 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: Fox Movies | Statement: [Fox Movies, hasBrand, Fox Movies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fox Movies
Context triple: [Fox Movies, hasBrand, Fox Movies]
  • A. Fox Movies chosen
    Fox Movies is a pay television movie channel brand known for broadcasting a wide range of Hollywood and international films across various global markets.
  • B. FX Movie Channel
    FX Movie Channel is an American pay television network specializing in airing commercial-free, uncut movies, often featuring a mix of contemporary and classic films.
  • C. Electric Pictures
    Electric Pictures is a film and television production company known for its work on the feature film "Hotel Mumbai."
  • D. CNN Films
    CNN Films is a documentary film division of CNN that produces and acquires non-fiction feature films for theatrical release and television broadcast.
  • E. 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.
  • 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_69d886cb581c8190ab05f4b429c9cd85 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d285f35881908c32b2f27ba7f0ac completed April 18, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc16fbdc819095411a056b9942c3 completed May 10, 2026, 7:27 p.m.
Created at: April 10, 2026, 5:32 a.m.