Triple

T20753048
Position Surface form Disambiguated ID Type / Status
Subject Meadowland E510779 entity
Predicate distributedBy P1951 FINISHED
Object Cinedigm NE NERFINISHED

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: Cinedigm | Statement: [Meadowland, distributedBy, Cinedigm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cinedigm
Context triple: [Meadowland, distributedBy, Cinedigm]
  • A. Cinedigm chosen
    Cinedigm is an American entertainment company that specializes in the distribution and streaming of independent films, documentaries, and niche content across digital and physical platforms.
  • B. Cinecom Entertainment Group
    Cinecom Entertainment Group was an American independent film distribution company known for releasing acclaimed art-house and foreign films during the 1980s and early 1990s.
  • C. Entertainment One
    Entertainment One is a multinational entertainment company known for producing and distributing films, television programming, and other media content worldwide.
  • D. Fandango Media
    Fandango Media is an American entertainment company best known for its online movie ticketing services and ownership of several film and TV review and streaming platforms.
  • E. Starz Entertainment
    Starz Entertainment is an American premium cable and streaming media company known for producing and distributing original television series and films.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c909ec8190b05987f1639513f6 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c22be6588190b137193cb3184fc0 completed April 21, 2026, 12:17 a.m.
Created at: April 16, 2026, 12:34 p.m.