Triple

T22436401
Position Surface form Disambiguated ID Type / Status
Subject Short Term 12 E554634 entity
Predicate distributor 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: [Short Term 12, distributor, Cinedigm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cinedigm
Context triple: [Short Term 12, distributor, 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. PVR Pictures
    PVR Pictures is an Indian film distribution and production company known for releasing a wide range of domestic and international movies in India.
  • C. 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.
  • D. Entertainment One
    Entertainment One is a multinational entertainment company known for producing and distributing films, television programming, and other media content worldwide.
  • E. 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.
  • 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_69e11e5010e48190ae1e9c9db9697637 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ade60508190b0100d5c2843b920 completed April 29, 2026, 1:11 a.m.
Created at: April 16, 2026, 8:47 p.m.