Triple

T11524164
Position Surface form Disambiguated ID Type / Status
Subject Chris Brinker E273245 entity
Predicate directed P7373 FINISHED
Object Bad Country E930138 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: Bad Country | Statement: [Chris Brinker, directed, Bad Country]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Country
Context triple: [Chris Brinker, directed, Bad Country]
  • A. Bad Country chosen
    Bad Country is a 2014 American crime thriller film about a contract killer who turns informant against a powerful crime syndicate.
  • B. Cruel Country
    Cruel Country is a 2022 double album by American rock band Wilco that explores country-inflected sounds through a loose, expansive song cycle.
  • C. Black Country
    The Black Country is an industrial region in the West Midlands of England historically known for coal mining, ironworking, and heavy manufacturing.
  • D. Men Without Country
    Men Without Country is a 1942 novel by Charles Nordhoff and James Norman Hall about Free French patriots fighting against Nazi occupation during World War II.
  • E. Mother Country
    "Mother Country" is a poem by Cuban-American writer Richard Blanco that reflects on themes of immigration, identity, and the complex notion of homeland.
  • 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_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d87fd26648819083de19bcddf8ad69 completed April 10, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6853dc47c81909d47f1047ba662e7 completed April 20, 2026, 7:57 p.m.
Created at: April 8, 2026, 9:37 p.m.