Triple

T5737982
Position Surface form Disambiguated ID Type / Status
Subject Lata Mangeshkar E126544 entity
Predicate influenced P9 FINISHED
Object Alka Yagnik E141143 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: Alka Yagnik | Statement: [Lata Mangeshkar, influenced, Alka Yagnik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alka Yagnik
Context triple: [Lata Mangeshkar, influenced, Alka Yagnik]
  • A. Alka Yagnik chosen
    Alka Yagnik is a renowned Indian playback singer celebrated for her melodious voice and numerous hit songs in Hindi cinema since the 1980s.
  • B. Asha Bhosle
    Asha Bhosle is a legendary Indian playback singer renowned for her versatile voice and vast repertoire across numerous film and non-film songs in multiple languages.
  • C. Shreya Ghoshal
    Shreya Ghoshal is a renowned Indian playback singer celebrated for her versatile voice and extensive work across multiple Indian film industries.
  • D. Lata Mangeshkar
    Lata Mangeshkar was a legendary Indian playback singer whose career spanned over seven decades and who became one of the most recorded and revered voices in the history of Indian music.
  • E. Sunidhi Chauhan
    Sunidhi Chauhan is a prominent Indian playback singer known for her powerful, versatile voice and numerous hit songs across Bollywood films.
  • 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_69c0083082288190b7478cead6b5430a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0255c8c308190821f968ec41c5078 completed March 22, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e10e4d08190bfb8162d53cfb443 completed March 22, 2026, 11:41 p.m.
Created at: March 22, 2026, 3:47 p.m.