Triple

T15935403
Position Surface form Disambiguated ID Type / Status
Subject Nainativu Nagapooshani Amman Temple E386428 entity
Predicate hasShrineFor P27875 FINISHED
Object Murugan E111277 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: Murugan | Statement: [Nainativu Nagapooshani Amman Temple, hasShrineFor, Murugan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Murugan
Context triple: [Nainativu Nagapooshani Amman Temple, hasShrineFor, Murugan]
  • A. Murugan chosen
    Murugan is a prominent Hindu deity of war and victory, especially revered in South India and Sri Lanka, often depicted as a youthful god with a spear and associated with wisdom and valor.
  • B. Duraimurugan
    Duraimurugan is an Indian politician from Tamil Nadu and a senior leader of the Dravida Munnetra Kazhagam (DMK) party.
  • C. Karpagambal
    Karpagambal is the Hindu goddess Parvati worshipped as the consort of Lord Shiva at the Kapaleeshwarar Temple in Mylapore, Chennai.
  • D. Ramanaidu
    Ramanaidu is an Indian given name most notably associated with D. Ramanaidu, a prominent Telugu film producer and founder of Suresh Productions.
  • E. Balakumaran
    Balakumaran was a prominent Indian Tamil author and screenwriter known for his popular novels and contributions to Tamil cinema.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156a8bbf48190ad10011e7eb0c6a9 completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3bfe72c819095f40a255bcd7ad5 completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:53 a.m.