Triple

T2244312
Position Surface form Disambiguated ID Type / Status
Subject Pampa E49466 entity
Predicate literaryInnovation P18315 FINISHED
Object adaptation of Sanskrit epic themes into Kannada 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: adaptation of Sanskrit epic themes into Kannada | Statement: [Pampa, literaryInnovation, adaptation of Sanskrit epic themes into Kannada]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: literaryInnovation
Context triple: [Pampa, literaryInnovation, adaptation of Sanskrit epic themes into Kannada]
  • A. literaryUniverse
    Indicates that two or more works of literature exist within the same fictional universe or continuity, sharing settings, characters, or canonical events.
  • B. inLiterature
    Indicates that a work, concept, or entity is mentioned, discussed, or represented within a piece of literature.
  • C. literaryInfluence chosen
    Indicates that one entity has had a significant impact on the style, themes, or development of another entity’s literary work.
  • D. literaryMovement
    Indicates the artistic or intellectual movement in literature with which a work, author, or text is associated or to which it belongs.
  • E. literaryLanguage
    Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
  • F. None of above.

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_69a88aa979788190ad6500f1d8eee2fc completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc0e8d5648190915ff689c7ca42bc completed March 7, 2026, 6:08 a.m.
PD Predicate disambiguation batch_69abbdb160248190aa75b38f11ad8602 completed March 7, 2026, 5:54 a.m.
Created at: March 4, 2026, 7:47 p.m.