Triple

T14711447
Position Surface form Disambiguated ID Type / Status
Subject FXM E345556 entity
Predicate formerName P65 FINISHED
Object Fox Movie Channel 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 Movie Channel | Statement: [FXM, formerName, Fox Movie Channel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fox Movie Channel
Context triple: [FXM, formerName, Fox Movie Channel]
  • 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. Fox Channel
    Fox Channel is an international entertainment television network known for airing a mix of popular TV series, movies, and original programming across various global markets.
  • C. Fox Kids
    Fox Kids was a popular American children's television programming block and network known for airing animated series and action-oriented shows during the 1990s and early 2000s.
  • D. The Movie Network
    The Movie Network was a Canadian premium television service known for broadcasting commercial-free movies, original series, and special event programming.
  • E. 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.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb982bf248190881e21a8a0861a3f completed April 14, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf08f2aa08190a5ac3240d1de90fb completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:28 a.m.