Triple

T10212973
Position Surface form Disambiguated ID Type / Status
Subject Taal E242375 entity
Predicate director P255 FINISHED
Object Subhash Ghai E405454 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: Subhash Ghai | Statement: [Taal, director, Subhash Ghai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Subhash Ghai
Context triple: [Taal, director, Subhash Ghai]
  • A. Subhash Ghai chosen
    Subhash Ghai is a prominent Indian film director, producer, and screenwriter known for directing several major Bollywood hits since the late 1970s.
  • B. Govind Nihalani
    Govind Nihalani is an acclaimed Indian cinematographer and filmmaker known for his work in parallel cinema and socially conscious films.
  • C. Hrishikesh Mukherjee
    Hrishikesh Mukherjee was a celebrated Indian film director and editor, best known for his warm, middle-class family dramas and comedies in Hindi cinema from the 1960s to the 1980s.
  • D. M.S. Sathyu
    M.S. Sathyu is an acclaimed Indian film director best known for his socially conscious and politically charged works, including the landmark film "Garm Hava," which helped define the parallel cinema movement.
  • E. Rakeysh Omprakash Mehra
    Rakeysh Omprakash Mehra is an acclaimed Indian filmmaker best known for directing socially charged and stylistically distinctive films such as "Rang De Basanti" and "Bhaag Milkha Bhaag."
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa23bce881909b5deac612ec22cb completed April 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d652e25be88190a6f1763e9e86666a completed April 8, 2026, 1:06 p.m.
Created at: April 6, 2026, 11:03 a.m.