Triple

T21979628
Position Surface form Disambiguated ID Type / Status
Subject Ramesh Powar E542801 entity
Predicate fullName P16 FINISHED
Object Ramesh Rajaram Powar 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: Ramesh Rajaram Powar | Statement: [Ramesh Powar, fullName, Ramesh Rajaram Powar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ramesh Rajaram Powar
Context triple: [Ramesh Powar, fullName, Ramesh Rajaram Powar]
  • A. Ramesh Powar chosen
    Ramesh Powar is a former Indian cricketer and off-spin bowler who represented India in international cricket and later became a coach.
  • B. Vijay Patkar
    Vijay Patkar is an Indian actor and comedian known for his supporting and character roles in Marathi and Hindi films.
  • C. Virendra Sharma
    Virendra Sharma is a British Labour Party politician who has served as the Member of Parliament for the London constituency of Ealing Southall.
  • D. Aravind Joshi
    Aravind Joshi was an Indian-American computer scientist and computational linguist known for pioneering work in formal grammar formalisms, particularly Tree Adjoining Grammars, and for foundational contributions to natural language processing.
  • E. Jaisingh Jadhav
    Jaisingh Jadhav is a fictional character known primarily as the central figure in the story of Kamala.
  • 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_69e0c48070988190909db97667b9a0ac completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1248bdd88819098bfeca550608f14 completed April 28, 2026, 9:20 p.m.
Created at: April 16, 2026, 8:03 p.m.