Triple

T16235703
Position Surface form Disambiguated ID Type / Status
Subject Ravi Kishan E394104 entity
Predicate notableWork P4 FINISHED
Object Bhojpuri cinema E173484 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: Bhojpuri cinema | Statement: [Ravi Kishan, notableWork, Bhojpuri cinema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bhojpuri cinema
Context triple: [Ravi Kishan, notableWork, Bhojpuri cinema]
  • A. Bhojpuri cinema chosen
    Bhojpuri cinema is the film industry that produces movies in the Bhojpuri language, primarily catering to audiences in the Bhojpuri-speaking regions of India and Nepal.
  • B. Chhattisgarhi cinema
    Chhattisgarhi cinema is the regional film industry that produces movies in the Chhattisgarhi language, reflecting the culture and stories of the Indian state of Chhattisgarh.
  • C. Bengali cinema
    Bengali cinema is the film industry producing movies in the Bengali language, renowned for its rich artistic tradition and influential auteurs such as Satyajit Ray.
  • D. Haryanvi cinema
    Haryanvi cinema is the regional film industry producing movies in the Haryanvi language, primarily serving audiences in the Indian state of Haryana and nearby regions.
  • E. Gujarati cinema
    Gujarati cinema is the film industry producing movies in the Gujarati language, primarily based in the Indian state of Gujarat and known for its regional storytelling and cultural themes.
  • 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_69d87f204df88190a8f88923decf9835 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2455abc608190ba3308c15c9e8a23 completed April 17, 2026, 2:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000ed8cbe48190be68ccade55211ad completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 5:04 a.m.