Triple

T29924423
Position Surface form Disambiguated ID Type / Status
Subject Media in Eritrea E760039 entity
Predicate pressFreedomIssues P48338 FINISHED
Object censorship 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: censorship | Statement: [Media in Eritrea, pressFreedomIssues, censorship]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: pressFreedomIssues
Context triple: [Media in Eritrea, pressFreedomIssues, censorship]
  • A. mediaFreedom
    Indicates the degree to which media outlets can operate, report, and express information without censorship, interference, or undue restriction.
  • B. censorshipIssues chosen
    Indicates that one entity imposes restrictions, suppression, or control over the information, expression, or content associated with another entity.
  • C. civilLibertiesPolicy
    Indicates a policy stance or action concerning the protection, restriction, or regulation of individuals’ civil liberties.
  • D. politicalFreedom
    Indicates the degree to which an entity allows or experiences rights to participate in political processes, express political views, and choose or influence governance without coercion or repression.
  • E. freedomImpacted
    Indicates that one entity’s freedom or autonomy is constrained, limited, or negatively affected by another factor or entity.
  • 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_69f224631674819080c8d089674f9f4f completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f67795fdd4819088f3c7d0de598699 completed May 2, 2026, 10:15 p.m.
PD Predicate disambiguation batch_69f66ec8298c8190b41fe9d182c05676 completed May 2, 2026, 9:38 p.m.
Created at: April 29, 2026, 6:15 p.m.