Triple

T16685638
Position Surface form Disambiguated ID Type / Status
Subject Subhash Ghai E405454 entity
Predicate hasWorkedWith P9615 FINISHED
Object Shah Rukh Khan 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: Shah Rukh Khan | Statement: [Subhash Ghai, hasWorkedWith, Shah Rukh Khan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shah Rukh Khan
Context triple: [Subhash Ghai, hasWorkedWith, Shah Rukh Khan]
  • A. Shah Rukh Khan chosen
    Shah Rukh Khan is a hugely influential Indian film actor and producer, often called the "King of Bollywood," known for his prolific career in Hindi cinema and global cultural impact.
  • B. Salman Khan
    Salman Khan is an American educator and entrepreneur best known as the founder of the online learning platform Khan Academy.
  • C. Salman Khan
    Salman Khan is a major Indian film actor and producer, known for his blockbuster Hindi movies, larger-than-life screen persona, and significant influence on Bollywood popular culture.
  • D. Aamir Khan
    Aamir Khan is a renowned Indian film actor, director, and producer known for his critically acclaimed and socially impactful movies in Bollywood.
  • E. Saif Ali Khan
    Saif Ali Khan is a prominent Indian film actor and producer known for his work in Hindi cinema and for being a member of the Pataudi royal family.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea550c0819085bd36c44237a61a completed April 18, 2026, 12:52 p.m.
Created at: April 10, 2026, 5:19 a.m.