Triple

T23439426
Position Surface form Disambiguated ID Type / Status
Subject Anushka Sharma E565353 entity
Predicate coStarredWith P14987 FINISHED
Object Varun Dhawan 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: Varun Dhawan | Statement: [Anushka Sharma, coStarredWith, Varun Dhawan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Varun Dhawan
Context triple: [Anushka Sharma, coStarredWith, Varun Dhawan]
  • A. Varun Dhawan chosen
    Varun Dhawan is a popular Indian film actor known for his work in contemporary Bollywood cinema, particularly in commercial comedies and dramas.
  • 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. Ranbir Kapoor
    Ranbir Kapoor is a prominent Indian film actor and producer known for his leading roles in contemporary Hindi cinema.
  • D. Aditya Sood
    Aditya Sood is a film producer known for his work on high-profile Hollywood projects, including the thriller-comedy "Cocaine Bear."
  • 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_69e24584f9488190bb32730bd2ce023e completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a5de713c8190b35bfa66dddbd5af completed April 29, 2026, 6:31 a.m.
Created at: April 17, 2026, 5:50 p.m.