Triple

T22093322
Position Surface form Disambiguated ID Type / Status
Subject Orphan: First Kill E545961 entity
Predicate cinematographyBy P1953 FINISHED
Object Karim Hussain 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: Karim Hussain | Statement: [Orphan: First Kill, cinematographyBy, Karim Hussain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karim Hussain
Context triple: [Orphan: First Kill, cinematographyBy, Karim Hussain]
  • A. Karim Hussain chosen
    Karim Hussain is a Canadian cinematographer and filmmaker known for his visually distinctive work on genre and horror films.
  • B. Shakir Mohamed
    Shakir Mohamed is a machine learning researcher known for his work in probabilistic modeling and artificial intelligence, including contributions at DeepMind.
  • C. Karim Sanjabi
    Karim Sanjabi was an influential Iranian nationalist politician, lawyer, and academic who became a leading figure of the National Front and a prominent opponent of the Pahlavi monarchy.
  • D. Karim Wade
    Karim Wade is a Senegalese politician and former government minister, widely known as the son and close political ally of former president Abdoulaye Wade.
  • E. Karim
    Karim is a French professional footballer widely recognized as one of the most prolific strikers of his generation.
  • 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128e6b1d881909bf0f4a52199354c completed April 28, 2026, 9:38 p.m.
Created at: April 16, 2026, 8:29 p.m.