Triple

T22033535
Position Surface form Disambiguated ID Type / Status
Subject Drishyam 2 E544144 entity
Predicate screenwriter P2831 FINISHED
Object Abhishek Pathak 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: Abhishek Pathak | Statement: [Drishyam 2, screenwriter, Abhishek Pathak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abhishek Pathak
Context triple: [Drishyam 2, screenwriter, Abhishek Pathak]
  • A. Abhishek Pathak chosen
    Abhishek Pathak is an Indian film producer and director known for backing and helming notable Hindi films, including acclaimed thrillers and dramas.
  • B. Aditya Sood
    Aditya Sood is a film producer known for his work on high-profile Hollywood projects, including the thriller-comedy "Cocaine Bear."
  • C. Nitesh Tiwari
    Nitesh Tiwari is an Indian film director and screenwriter best known for helming the blockbuster biographical sports drama "Dangal" and the coming-of-age hit "Chhichhore."
  • D. Vikrant Kapoor
    Vikrant Kapoor is the central male protagonist in the 1999 Bollywood musical romance film "Taal," portrayed by actor Akshaye Khanna.
  • E. Manish Bhasin
    Manish Bhasin is a British sports journalist and television presenter best known for his long-running work on BBC football coverage.
  • 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_69e11e2f98c8819083e11eab90942a78 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127ef97348190b8dcdcad11694ebe completed April 28, 2026, 9:34 p.m.
Created at: April 16, 2026, 8:24 p.m.