Triple

T22075893
Position Surface form Disambiguated ID Type / Status
Subject Naushad E545519 entity
Predicate workedWith P398 FINISHED
Object Talat Mahmood 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: Talat Mahmood | Statement: [Naushad, workedWith, Talat Mahmood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Talat Mahmood
Context triple: [Naushad, workedWith, Talat Mahmood]
  • A. Talat Mahmood chosen
    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.
  • B. Mohammed Rafi
    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.
  • C. Aftab Iqbal
    Aftab Iqbal was the son of the renowned philosopher-poet Allama Muhammad Iqbal and a Pakistani academic and literary figure in his own right.
  • D. 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.
  • E. 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.
  • 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_69e11e3523488190badd54b5d580c00d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128b1904881909a1769ce8be39e05 completed April 28, 2026, 9:37 p.m.
Created at: April 16, 2026, 8:28 p.m.