Triple

T15676569
Position Surface form Disambiguated ID Type / Status
Subject Lara Dutta E377457 entity
Predicate hasChild P369 FINISHED
Object Saira Bhupathi E1126032 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: Saira Bhupathi | Statement: [Lara Dutta, hasChild, Saira Bhupathi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saira Bhupathi
Context triple: [Lara Dutta, hasChild, Saira Bhupathi]
  • A. Sania Mirza
    Sania Mirza is a renowned Indian professional tennis player, widely regarded as one of the country’s greatest female athletes and a multiple Grand Slam doubles champion.
  • B. Pradeep Sindhu
    Pradeep Sindhu is an Indian-American computer scientist and entrepreneur best known as the co-founder and former chief technology officer of networking company Juniper Networks.
  • C. Mahesh Bhupathi chosen
    Mahesh Bhupathi is a former Indian professional tennis player renowned as one of the country’s most successful doubles specialists, with multiple Grand Slam titles to his name.
  • D. Sandhini Agarwal
    Sandhini Agarwal is an AI researcher known for her work at OpenAI on safety, policy, and the development and deployment of large-scale models such as CLIP.
  • E. Padmanee Sharma
    Padmanee Sharma is an American oncologist and immunologist known for her pioneering research in cancer immunotherapy and checkpoint blockade.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f2e10a4819097eba1ea31e36ac2 completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ee0446881909e9c2504d51d49a3 completed May 9, 2026, 5:29 p.m.
Created at: April 10, 2026, 4:16 a.m.