Triple

T20168615
Position Surface form Disambiguated ID Type / Status
Subject Jwalamukhi Temple E491893 entity
Predicate associatedWith P37 FINISHED
Object Navadurga NE NERFINISHED

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: Navadurga | Statement: [Jwalamukhi Temple, associatedWith, Navadurga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Navadurga
Context triple: [Jwalamukhi Temple, associatedWith, Navadurga]
  • A. Navadurga chosen
    Navadurga refers to the nine manifestations of the Hindu goddess Durga, each worshipped on a different day of the Navaratri festival.
  • B. Gorikot
    Gorikot is a village and local hub in Pakistan’s Astore Valley, serving as a gateway to nearby mountain regions and trekking routes.
  • C. Pavagada
    Pavagada is a town in the Tumakuru district of Karnataka, India, known for its large solar park and semi-arid landscape.
  • D. Lakkundi
    Lakkundi is a historic village in Karnataka, India, renowned for its intricately carved medieval temples and stepwells built during the Western Chalukya period.
  • E. Channapatna
    Channapatna is a town in Karnataka, India, renowned for its traditional wooden toy-making industry and vibrant lacquerware crafts.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66846f4ec81908b0dc6a6e0ec27dd completed April 20, 2026, 5:54 p.m.
Created at: April 11, 2026, 11:35 p.m.