Triple

T34976073
Position Surface form Disambiguated ID Type / Status
Subject Krakozhian E1008679 entity
Predicate hasAssociatedFictionalGovernment P147883 FINISHED
Object Krakozhian government NE NERFINISHED

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: Krakozhian government | Statement: [Krakozhian, hasAssociatedFictionalGovernment, Krakozhian government]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAssociatedFictionalGovernment
Context triple: [Krakozhian, hasAssociatedFictionalGovernment, Krakozhian government]
  • A. hasFictionalGovernmentAgency
    Indicates that an entity includes, features, or is associated with a government agency that is fictional rather than real.
  • B. hasFictionalAdministration chosen
    Indicates that an entity is governed, managed, or overseen by an administration that is fictional rather than real.
  • C. hasFictionalLeader
    Indicates that an entity is led or governed by a leader who is a fictional character rather than a real person.
  • D. governedByFictional
    Indicates that one entity is under the rule, control, or authority of another entity that is fictional or exists only in an imagined context.
  • E. hasFictionalOffice
    Indicates that one entity maintains or is associated with an office or workplace that exists only in a fictional or imaginary context.
  • 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_69f76dc78a308190a1ac29ad4a9a4895 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcf825ca7081909d06b0df33eb33f9 completed May 7, 2026, 8:37 p.m.
PD Predicate disambiguation batch_69fcf42160f0819096812a8bf590875e completed May 7, 2026, 8:20 p.m.
Created at: May 3, 2026, 4:01 p.m.