Triple

T3842684
Position Surface form Disambiguated ID Type / Status
Subject Greg Abel E93488 entity
Predicate hasColleague P398 FINISHED
Object Ajit Jain E79835 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: Ajit Jain | Statement: [Greg Abel, hasColleague, Ajit Jain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ajit Jain
Context triple: [Greg Abel, hasColleague, Ajit Jain]
  • A. Ajit Jain chosen
    Ajit Jain is an Indian-American business executive best known as a top insurance lieutenant and potential successor to Warren Buffett at Berkshire Hathaway.
  • B. Satish Jain
    Satish Jain is an Indian economist and academic known for his contributions to economic theory and his association with the Delhi School of Economics.
  • C. Sanjay Jain
    Sanjay Jain is an economist recognized for his academic contributions and scholarship associated with the Delhi School of Economics.
  • D. Vijay Joshi
    Vijay Joshi is an Indian economist known for his influential work on macroeconomic policy and development, particularly in the context of the Indian economy.
  • E. Ashok Arora
    Ashok Arora is an Indian entrepreneur best known as one of the co-founders of the global IT services and consulting company Infosys.
  • 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_69aed96ce578819084ab16e3439976c9 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeebb397ac81908f74a42a0eeb8682 completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5122ba6a4819099986e50f42f2a92 completed March 14, 2026, 7:45 a.m.
Created at: March 9, 2026, 3:18 p.m.