Triple

T16463561
Position Surface form Disambiguated ID Type / Status
Subject Politics of Uzbekistan E399869 entity
Predicate reformTrend P105600 FINISHED
Object gradual political and economic reforms since 2016 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: gradual political and economic reforms since 2016 | Statement: [Politics of Uzbekistan, reformTrend, gradual political and economic reforms since 2016]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: reformTrend
Context triple: [Politics of Uzbekistan, reformTrend, gradual political and economic reforms since 2016]
  • A. reform
    Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
  • B. typeOfReforms
    Indicates the specific kinds or categories of reforms associated with an entity or situation.
  • C. relatedReforms
    Indicates that one reform is connected or associated with another reform, typically through shared goals, content, or impact.
  • D. associatedReforms chosen
    Indicates a relationship where certain reforms are linked or connected to a given entity, such as a policy, event, or individual.
  • E. notableReform
    Indicates that an entity is recognized for having initiated, led, or been central to a significant reform or transformative change in a system, policy, or institution.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d83687081908450657e1da6f6af completed April 18, 2026, 7:06 a.m.
PD Predicate disambiguation batch_69e227048d608190a4205eae3117629a completed April 17, 2026, 12:26 p.m.
Created at: April 10, 2026, 5:10 a.m.