Triple

T1409843
Position Surface form Disambiguated ID Type / Status
Subject D. Udaya Kumar E31778 entity
Predicate name P16 FINISHED
Object D. Udaya Kumar E31778 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: D. Udaya Kumar | Statement: [D. Udaya Kumar, name, D. Udaya Kumar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: D. Udaya Kumar
Context triple: [D. Udaya Kumar, name, D. Udaya Kumar]
  • A. D. Udaya Kumar chosen
    D. Udaya Kumar is an Indian academic and designer best known for creating the modern symbol of the Indian rupee currency.
  • B. K. Balaji
    K. Balaji was an Indian film producer and actor known for his work in Tamil cinema and for producing several successful remakes of Hindi films.
  • C. Allu Aravind
    Allu Aravind is a prominent Indian film producer and distributor, best known for founding the production company Geetha Arts and producing numerous successful Telugu and Hindi films.
  • D. N. T. Rama Rao Jr.
    N. T. Rama Rao Jr. is a prominent Indian film actor known for his leading roles in Telugu cinema and his dynamic performances in action and drama films.
  • E. Sukumar
    Sukumar is a prominent Indian film director and screenwriter known for his psychologically layered storytelling and stylish Telugu-language films in the Tollywood industry.
  • 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_69a49918e1f88190ba610f9dc8114578 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c3e0bfd08190a50820bc7585c28f completed March 1, 2026, 10:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad293cb8f0819085bea7914abf0683 completed March 8, 2026, 7:46 a.m.
Created at: March 1, 2026, 7:59 p.m.