Triple

T8636033
Position Surface form Disambiguated ID Type / Status
Subject Maneka Gandhi E204524 entity
Predicate birthName P65 FINISHED
Object Maneka Anand E204524 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: Maneka Anand | Statement: [Maneka Gandhi, birthName, Maneka Anand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maneka Anand
Context triple: [Maneka Gandhi, birthName, Maneka Anand]
  • A. Maneka Gandhi chosen
    Maneka Gandhi is an Indian politician, animal rights activist, and longtime member of parliament known for her work on environmental and animal welfare issues.
  • B. Anu Khosla
    Anu Khosla is one of the children of Indian-American billionaire venture capitalist and Sun Microsystems co-founder Vinod Khosla.
  • C. Neena Gupta
    Neena Gupta is an acclaimed Indian film, television, and theatre actress and director known for her versatile performances across parallel and mainstream cinema.
  • D. Meena Khadikar
    Meena Khadikar is an Indian playback singer and composer, known for her work in Marathi and Hindi music and as a member of the renowned Mangeshkar musical family.
  • E. Suhasini Mulay
    Suhasini Mulay is an Indian actress and documentary filmmaker known for her work in parallel cinema and acclaimed character roles in Hindi and regional 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_69ca834b903c8190add96cc651e1a477 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4760fa448190862c886bc5a6ec10 completed March 31, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef354c5c08190bf7d3023a3473d2f completed April 2, 2026, 10:53 p.m.
Created at: March 30, 2026, 6:27 p.m.