Triple

T20381934
Position Surface form Disambiguated ID Type / Status
Subject Arkadyevich E497854 entity
Predicate fictionalUsage P50195 FINISHED
Object Russian literature 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: Russian literature | Statement: [Arkadyevich, fictionalUsage, Russian literature]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalUsage
Context triple: [Arkadyevich, fictionalUsage, Russian literature]
  • A. fictionalUse chosen
    Indicates that one entity makes use of another within a fictional or imaginary context, rather than in real-world usage.
  • B. fictionalizationOf
    Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
  • C. fictionalFocus
    Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
  • D. fictionalContent
    Indicates that one entity is content whose subject matter, events, or characters are imaginary or invented rather than factual.
  • E. fictionalOrigin
    Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
  • 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_69e0b4a5b7908190a972e4e7e698ae94 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e678b0ee708190bdbe4aab28a61525 completed April 20, 2026, 7:04 p.m.
PD Predicate disambiguation batch_69e57648be3c81908256838228cabf5c completed April 20, 2026, 12:41 a.m.
Created at: April 16, 2026, 11:27 a.m.