Triple

T14765786
Position Surface form Disambiguated ID Type / Status
Subject Bad Words E346991 entity
Predicate starring P1507 FINISHED
Object Rohan Chand E863631 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: Rohan Chand | Statement: [Bad Words, starring, Rohan Chand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rohan Chand
Context triple: [Bad Words, starring, Rohan Chand]
  • A. Rohan Chand chosen
    Rohan Chand is an American child actor best known for his lead role as Mowgli in the film "Mowgli: Legend of the Jungle" and appearances in movies like "Bad Words" and "Lone Survivor."
  • B. Rohan Murty
    Rohan Murty is an Indian computer scientist, entrepreneur, and philanthropist, known for founding the Murty Classical Library of India and for his work in technology and academia.
  • C. Jay Chaudhry
    Jay Chaudhry is an Indian-American entrepreneur and billionaire best known as the founder and CEO of the cloud security company Zscaler.
  • D. Divyank Turakhia
    Divyank Turakhia is an Indian serial tech entrepreneur and billionaire best known for building and selling multiple internet and ad-tech companies, including those under the Directi Group.
  • E. Naveen Andrews
    Naveen Andrews is a British actor best known for his roles in the television series "Lost" and films such as "The English Patient."
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7f576c881909da70627f5897c94 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cf4cef081909fa62125f43b36bc completed May 8, 2026, 4:19 p.m.
Created at: April 10, 2026, 1:30 a.m.