Triple

T34150678
Position Surface form Disambiguated ID Type / Status
Subject Kamika Ekadashi E875984 entity
Predicate religiousMeritTerm P199957 FINISHED
Object punya LITERAL 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: punya | Statement: [Kamika Ekadashi, religiousMeritTerm, punya]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: religiousMeritTerm
Context triple: [Kamika Ekadashi, religiousMeritTerm, punya]
  • A. religiousTitle
    Indicates that one entity holds or is referred to by a specific religious rank, honorific, or clerical title in relation to another entity.
  • B. pietyReputation
    Indicates the degree to which an entity is regarded as devout, virtuous, or religiously upright based on its perceived behavior or character.
  • C. eraOfReligiousFunction
    Indicates the historical time period during which a religious role, office, or function was actively performed or held.
  • D. hasReligiousRoleEquivalent
    Indicates that two religious roles are considered functionally or hierarchically equivalent within or across religious traditions.
  • E. religiousTextRole
    Indicates the specific role or function that a religious text has in relation to a person, group, practice, or tradition.
  • F. None of above. chosen

Provenance (4 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_69f349abaa508190a820f206620efddc completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69ff65987ff88190b09be64f7c0e1da9 completed May 9, 2026, 4:49 p.m.
PD Predicate disambiguation batch_69ff6525b0548190bef7a9f009e00bb8 completed May 9, 2026, 4:47 p.m.
PDg Predicate description generation batch_69ff659717708190bb56714d1b261063 completed May 9, 2026, 4:49 p.m.
Created at: May 1, 2026, 1:54 a.m.