Triple

T1565287
Position Surface form Disambiguated ID Type / Status
Subject Azim Premji Foundation E33418 entity
Predicate foundedBy P104 FINISHED
Object Azim Premji E5073 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: Azim Premji | Statement: [Azim Premji Foundation, foundedBy, Azim Premji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Azim Premji
Context triple: [Azim Premji Foundation, foundedBy, Azim Premji]
  • A. Azim Premji chosen
    Azim Premji is an Indian business tycoon and philanthropist, best known as the longtime chairman of Wipro and one of the world’s leading charitable donors.
  • B. Rishad Premji
    Rishad Premji is an Indian business executive who serves as the chairman of Wipro Limited, one of India’s leading global IT services companies.
  • C. Mohamed Premji
    Mohamed Premji was an Indian industrialist and entrepreneur best known as the founder of Wipro, which he built into a major business conglomerate.
  • D. N. R. Narayana Murthy
    N. R. Narayana Murthy is an Indian billionaire businessman best known as the co-founder of Infosys, a pioneering global IT services company.
  • E. Gagan Biyani
    Gagan Biyani is an entrepreneur best known as a co-founder of the online learning platform Udemy and for his work in the education technology sector.
  • 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_69a885f11b048190935025a035302715 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa621242188190a7e1deeada7688d8 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad68079e448190b71c2cd194abeb86 completed March 8, 2026, 12:13 p.m.
Created at: March 4, 2026, 7:27 p.m.