Triple

T22147011
Position Surface form Disambiguated ID Type / Status
Subject K. Asif E547311 entity
Predicate fullName P16 FINISHED
Object Kamal Amrohi Asif 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: Kamal Amrohi Asif | Statement: [K. Asif, fullName, Kamal Amrohi Asif]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kamal Amrohi Asif
Context triple: [K. Asif, fullName, Kamal Amrohi Asif]
  • A. Kamal Amrohi chosen
    Kamal Amrohi was a renowned Indian film director, screenwriter, and producer best known for classic Hindi cinema works such as "Mahal" and "Pakeezah."
  • B. Mehboob
    Mehboob is an Indian lyricist best known for his work on popular Bollywood film soundtracks in the 1990s and 2000s.
  • C. I. S. Johar
    I. S. Johar was an Indian actor, writer, and filmmaker known for his character roles in both Hindi cinema and international films, including the epic historical drama "Lawrence of Arabia."
  • D. Khwaja Ahmad Abbas
    Khwaja Ahmad Abbas was an influential Indian writer, journalist, and film director known for his socially conscious stories and collaborations with filmmakers like Raj Kapoor.
  • E. Kamal Pandey
    Kamal Pandey is an Indian screenwriter best known for his work on Hindi films such as the romantic comedy-drama "Qarib Qarib Singlle."
  • 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_69e11e3a95d88190a3bd80d9471976c3 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129f156988190bc9a24a37418e849 completed April 28, 2026, 9:43 p.m.
Created at: April 16, 2026, 8:33 p.m.