Triple

T3852831
Position Surface form Disambiguated ID Type / Status
Subject Letter to Serapion E85336 entity
Predicate religiousLiteraryForm P6480 FINISHED
Object epistolary treatise 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: epistolary treatise | Statement: [Letter to Serapion, religiousLiteraryForm, epistolary treatise]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: religiousLiteraryForm
Context triple: [Letter to Serapion, religiousLiteraryForm, epistolary treatise]
  • A. hasLiteraryForm chosen
    Indicates that one entity is expressed, structured, or realized in a particular literary form (such as a genre, style, or textual format).
  • B. religiousTextOf
    Indicates that one entity is a religious text that is sacred to, foundational for, or primarily associated with another entity (such as a religion, denomination, or faith community).
  • C. religiousTextTradition
    Indicates that a religious text is associated with, originates from, or is authoritative within a particular religious tradition or denomination.
  • D. literarySubject
    Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
  • E. literaryUnit
    Indicates that one entity is a distinct segment or component (such as a chapter, scene, or passage) within a larger literary work or text.
  • 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec01f7b48190ba1ec89328b3fccb completed March 9, 2026, 3:49 p.m.
PD Predicate disambiguation batch_69aee750377c8190af70c79768c0edd8 completed March 9, 2026, 3:29 p.m.
Created at: March 9, 2026, 3:19 p.m.