Triple

T6100925
Position Surface form Disambiguated ID Type / Status
Subject Carroll Ballard E135991 entity
Predicate directed P7373 FINISHED
Object Duma E569897 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: Duma | Statement: [Carroll Ballard, directed, Duma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Duma
Context triple: [Carroll Ballard, directed, Duma]
  • A. Duma chosen
    Duma is a 2005 family adventure film directed by Carroll Ballard about a boy and his close bond with an orphaned cheetah in South Africa.
  • B. Barbusse
    Barbusse is the surname of Henri Barbusse, a French novelist and pacifist best known for his World War I novel "Le Feu" ("Under Fire").
  • C. Zyuzino
    Zyuzino is a Moscow Metro station on the Big Circle Line serving the Zyuzino District in southern Moscow.
  • D. Darrow
    Darrow is a surname most famously associated with Clarence Darrow, the prominent American lawyer and civil libertarian known for high-profile cases in the early 20th century.
  • E. Dalstroi
    Dalstroi was a Soviet state organization that managed forced labor camps and large-scale industrial and construction projects in the Kolyma region, particularly focused on gold mining.
  • 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_69c0087dee9881909e3655be88208c01 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05b3aa9908190865be98ada141d37 completed March 22, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1358d0e18819084e2acb9e75271b4 completed March 23, 2026, 12:43 p.m.
Created at: March 22, 2026, 4:13 p.m.