Triple

T7730611
Position Surface form Disambiguated ID Type / Status
Subject Viranarasimha Raya E175239 entity
Predicate title P38 FINISHED
Object Maharaya E669614 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: Maharaya | Statement: [Viranarasimha Raya, title, Maharaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maharaya
Context triple: [Viranarasimha Raya, title, Maharaya]
  • A. Maharaya chosen
    Maharaya is a royal title associated with Achyuta Deva Raya, a 16th-century ruler of the Vijayanagara Empire in South India.
  • B. Umrangso
    Umrangso is an industrial and commercial town in Assam, India, known for its cement factories and hydroelectric power projects.
  • C. Siya
    Siya is an alternate name for the Avatime language, a Kwa language spoken in the Volta Region of Ghana.
  • D. Madura
    Madura is an island off the northeastern coast of Java in Indonesia, known for its distinct Madurese culture and traditional bull races.
  • E. Tan Malaka
    Tan Malaka was an influential Indonesian Marxist thinker, revolutionary leader, and nationalist who played a key role in the struggle against Dutch colonial rule and in shaping early Indonesian political thought.
  • 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703358cf881909df8496d943d6de7 completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b52e176481908595fea4ace7a607 completed March 29, 2026, 5:14 a.m.
Created at: March 27, 2026, 4:06 p.m.