Triple

T18633339
Position Surface form Disambiguated ID Type / Status
Subject Klamm E455475 entity
Predicate literaryThemeContext P55714 FINISHED
Object bureaucracy 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: bureaucracy | Statement: [Klamm, literaryThemeContext, bureaucracy]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: literaryThemeContext
Context triple: [Klamm, literaryThemeContext, bureaucracy]
  • A. literaryThemeInvolvement
    Indicates the involvement or presence of a particular literary theme within a work, passage, or character arc.
  • B. hasLiteraryContext chosen
    Indicates that something is associated with, situated within, or explained by a particular literary context (such as a work, genre, period, or interpretive framework).
  • C. literarySubject
    Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
  • D. literaryMuseOf
    Indicates a relationship in which one entity serves as the creative inspiration or muse for another entity’s literary work.
  • E. literaryCenter
    Indicates that a location functions as a primary hub or focal point for literary activity, such as writing, publishing, or literary culture.
  • 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_69d8d38cc7948190a55ea64e5638994e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54fc5c7ec8190ab0c64f009583f96 completed April 19, 2026, 9:57 p.m.
PD Predicate disambiguation batch_69e478d4a7948190a4bb9223bb5dddfc completed April 19, 2026, 6:40 a.m.
Created at: April 10, 2026, 11:46 a.m.