Triple

T932949
Position Surface form Disambiguated ID Type / Status
Subject Dvaita E20133 entity
Predicate primaryDeity P7648 FINISHED
Object Narayana E131832 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: Narayana | Statement: [Dvaita, primaryDeity, Narayana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Narayana
Context triple: [Dvaita, primaryDeity, Narayana]
  • A. Narayana chosen
    Narayana is a revered name of the Hindu god Vishnu, especially associated with his role as the supreme preserver and sustainer of the universe.
  • B. Shankara
    Shankara is a revered epithet of the Hindu god Shiva, highlighting his role as a benevolent and auspicious divine benefactor.
  • C. Vinayaka
    Vinayaka is another name for the Hindu deity Ganesha, the elephant-headed god revered as the remover of obstacles and patron of wisdom and beginnings.
  • D. Kalki
    Kalki is the prophesied future incarnation of the Hindu god Vishnu who is foretold to appear at the end of the current age to restore righteousness and cosmic order.
  • E. Jagat Narayan
    Jagat Narayan was an Indian educationist and public figure who served as a member of the British-era Hunter Commission on education reforms.
  • 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_69a493af3dc48190adb7263e6e445ea1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3627ccc8190a836515b2ea85ec5 completed March 1, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac82f9610c819094bc8d9e5f242816 completed March 7, 2026, 7:56 p.m.
Created at: March 1, 2026, 7:40 p.m.