Triple

T17425944
Position Surface form Disambiguated ID Type / Status
Subject Berezhany Raion E423736 entity
Predicate wasPartOfReform P24524 FINISHED
Object reduction of number of raions in Ternopil Oblast 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: reduction of number of raions in Ternopil Oblast | Statement: [Berezhany Raion, wasPartOfReform, reduction of number of raions in Ternopil Oblast]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: wasPartOfReform
Context triple: [Berezhany Raion, wasPartOfReform, reduction of number of raions in Ternopil Oblast]
  • A. isPartOfReform chosen
    Indicates that an action, measure, or component belongs to, contributes to, or is included within a broader reform initiative or process.
  • B. advocatedReformOf
    Indicates that one entity publicly supported or promoted changes to another entity, typically aiming to improve or modify its structure, policies, or practices.
  • C. replacedInReform
    Indicates that one entity was substituted or superseded by another as part of a formal reform or restructuring process.
  • D. reform
    Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
  • E. reformInfluencedBy
    Indicates that a reform was shaped, guided, or significantly affected by another person, idea, event, or reform.
  • 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e448fbfda88190be1c001d64289bf7 completed April 19, 2026, 3:16 a.m.
PD Predicate disambiguation batch_69e3b030eac481909b8402719cc3102e completed April 18, 2026, 4:24 p.m.
Created at: April 10, 2026, 5:46 a.m.