Triple

T13652507
Position Surface form Disambiguated ID Type / Status
Subject Salil Parekh E326774 entity
Predicate fullName P16 FINISHED
Object Salil Satish Parekh E326773 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: Salil Satish Parekh | Statement: [Salil Parekh, fullName, Salil Satish Parekh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salil Satish Parekh
Context triple: [Salil Parekh, fullName, Salil Satish Parekh]
  • A. Utsav Parekh
    Utsav Parekh is an Indian businessman and sports investor best known as a co-owner of the Indian Super League football club Atlético de Kolkata.
  • B. Salil Parekh chosen
    Salil Parekh is an Indian business executive who serves as the CEO and Managing Director of Infosys, one of the world’s leading IT services and consulting companies.
  • C. Ronnie Irani
    Ronnie Irani is a former English all-rounder who played county cricket for Essex and represented England in both Test and One Day International matches.
  • D. Deepak Kapur
    Deepak Kapur is a computer scientist known for his influential work in automated reasoning and term rewriting systems.
  • E. Mahesh Manjrekar
    Mahesh Manjrekar is an Indian filmmaker and actor known for his influential work in Marathi and Hindi cinema, including directing acclaimed films like "Vaastav."
  • 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_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc609676c8190b5b1cabe6b315142 completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d46c48c81908d64f1a32cf08c5b completed May 3, 2026, 7:08 p.m.
Created at: April 9, 2026, 9:52 p.m.