Triple

T19273774
Position Surface form Disambiguated ID Type / Status
Subject Welcome to Sajjanpur E481993 entity
Predicate castMember P1668 FINISHED
Object Ravi Kishan 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: Ravi Kishan | Statement: [Welcome to Sajjanpur, castMember, Ravi Kishan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ravi Kishan
Context triple: [Welcome to Sajjanpur, castMember, Ravi Kishan]
  • A. Ravi Kishan chosen
    Ravi Kishan is an Indian actor, film producer, and politician best known for his work in Bhojpuri cinema as well as Hindi and Telugu films.
  • B. Rajkummar Rao
    Rajkummar Rao is an acclaimed Indian film actor known for his versatile performances in Hindi cinema, particularly in critically praised independent and mainstream films.
  • C. Varun Dhawan
    Varun Dhawan is a popular Indian film actor known for his work in contemporary Bollywood cinema, particularly in commercial comedies and dramas.
  • D. Manish Bhasin
    Manish Bhasin is a British sports journalist and television presenter best known for his long-running work on BBC football coverage.
  • E. Shahid Kapoor
    Shahid Kapoor is a popular Indian film actor known for his versatile performances in Hindi cinema, including acclaimed roles in films like "Jab We Met," "Haider," and "Kabir Singh."
  • 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_69d8e8ce54cc8190998418ff1f66ef28 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fbba7758819081c1c78667c59c5e completed April 20, 2026, 10:11 a.m.
Created at: April 10, 2026, 1:29 p.m.