Triple

T3759645
Position Surface form Disambiguated ID Type / Status
Subject Good Night, and Good Luck E82129 entity
Predicate distributor P1951 FINISHED
Object Warner Independent Pictures E317046 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: Warner Independent Pictures | Statement: [Good Night, and Good Luck, distributor, Warner Independent Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Warner Independent Pictures
Context triple: [Good Night, and Good Luck, distributor, Warner Independent Pictures]
  • A. Warner Independent Pictures chosen
    Warner Independent Pictures was a specialty film division of Warner Bros. focused on producing and distributing independent and art-house films.
  • B. Gramercy Pictures
    Gramercy Pictures was an American film production and distribution company known for releasing acclaimed independent and specialty films in the 1990s.
  • C. Warner Sogefilms
    Warner Sogefilms is a Spanish film distribution company associated with releasing major domestic and international titles.
  • D. Warner Bros. Pictures
    Warner Bros. Pictures is a major American film production and distribution studio known for releasing numerous blockbuster movies across a wide range of genres.
  • E. Alliance Films
    Alliance Films was a major Canadian film distribution and production company known for releasing a wide range of independent and international movies in Canada and other markets.
  • 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_69ad8b1db40081908b61ffa6b78afd4d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcbc3d3f48190974cec104080949f completed March 8, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb0fc6248190b2f4adf3fd2d73d9 completed March 14, 2026, 6:07 a.m.
Created at: March 8, 2026, 3:35 p.m.