Triple

T19233339
Position Surface form Disambiguated ID Type / Status
Subject Old Lane Partners E480924 entity
Predicate foundedBy P104 FINISHED
Object Vikram Pandit 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: Vikram Pandit | Statement: [Old Lane Partners, foundedBy, Vikram Pandit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vikram Pandit
Context triple: [Old Lane Partners, foundedBy, Vikram Pandit]
  • A. Vikram Pandit chosen
    Vikram Pandit is an Indian-American banker best known for serving as the CEO of Citigroup during the global financial crisis.
  • 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. Sanjay Singhania
    Sanjay Singhania is the amnesiac protagonist of the Indian film "Ghajini," known for using tattoos and photographs to track down his fiancée’s killer.
  • D. Natarajan Chandrasekaran
    Natarajan Chandrasekaran is an Indian business executive who serves as the chairman of Tata Sons, the holding company of the Tata Group.
  • E. Nusli Wadia
    Nusli Wadia is an Indian industrialist and chairman of the Wadia Group, known for leading major companies such as Bombay Dyeing and Britannia Industries.
  • 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_69d8e8ccb8f48190ad420098e74fb1db completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fa9fa7348190947129273d19c9a7 completed April 20, 2026, 10:06 a.m.
Created at: April 10, 2026, 1:25 p.m.