Triple

T16046877
Position Surface form Disambiguated ID Type / Status
Subject Polska Ludowa E389243 entity
Predicate kontrolaMediów P121753 FINISHED
Object cenzura państwowa 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: cenzura państwowa | Statement: [Polska Ludowa, kontrolaMediów, cenzura państwowa]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: kontrolaMediów
Context triple: [Polska Ludowa, kontrolaMediów, cenzura państwowa]
  • A. mediaCenter
    Indicates a relationship where an entity functions as or is associated with a media center, typically serving as a hub for managing, distributing, or accessing media content.
  • B. mediatisedBy
    Indicates that an entity’s communication or interaction is conveyed, shaped, or influenced through a particular medium or media channel rather than occurring directly.
  • C. mediaFocus
    Indicates that the primary attention, coverage, or emphasis of a media source is directed toward a particular entity or topic.
  • D. mediaConsumption
    Indicates the act or pattern of engaging with, using, or experiencing media content (such as watching, listening, or reading).
  • E. mediaExposure
    Indicates the extent to which an entity is subjected to or receives attention from media channels such as television, radio, print, or online platforms.
  • F. None of above. chosen

Provenance (4 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1ff63edb0819092cbb671967bbdcd completed April 17, 2026, 9:37 a.m.
PD Predicate disambiguation batch_69e1826f34c081908005bb736f1c485d completed April 17, 2026, 12:44 a.m.
PDg Predicate description generation batch_69e1ff5cd7e481908a29214139a3de2e completed April 17, 2026, 9:37 a.m.
Created at: April 10, 2026, 4:56 a.m.