Triple

T22663292
Position Surface form Disambiguated ID Type / Status
Subject Asha Bhosle E559717 entity
Predicate collaboratedWith P435 FINISHED
Object Mohammed Rafi 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: Mohammed Rafi | Statement: [Asha Bhosle, collaboratedWith, Mohammed Rafi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mohammed Rafi
Context triple: [Asha Bhosle, collaboratedWith, Mohammed Rafi]
  • A. Mohammed Rafi chosen
    Mohammed Rafi was a legendary Indian playback singer renowned for his extraordinary vocal range and versatility, who became one of the most iconic voices in Hindi cinema.
  • B. Kishore Kumar
    Kishore Kumar was a legendary Indian playback singer, actor, and music composer renowned for his versatile voice and iconic songs in Hindi cinema.
  • C. Talat Mahmood
    Talat Mahmood was a renowned Indian playback singer and ghazal vocalist, celebrated for his velvety voice and soulful, romantic songs in mid-20th-century Hindi cinema.
  • D. Udit Narayan
    Udit Narayan is a renowned Indian playback singer celebrated for his melodious voice and numerous hit songs in Bollywood films since the 1980s.
  • E. Dilip Kumar
    Dilip Kumar was a legendary Indian film actor, celebrated as the "Tragedy King" of Hindi cinema and renowned for his intense, nuanced performances in classic Bollywood films.
  • 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_69e2454a158c819093b8e35f5045efb6 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f17660c0c88190bed9fa8f6517eec4 completed April 29, 2026, 3:09 a.m.
Created at: April 17, 2026, 3:08 p.m.