Triple

T29440115
Position Surface form Disambiguated ID Type / Status
Subject Archins E746687 entity
Predicate writingSystemUsedForLanguage P26603 FINISHED
Object Cyrillic script 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: Cyrillic script | Statement: [Archins, writingSystemUsedForLanguage, Cyrillic script]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: writingSystemUsedForLanguage
Context triple: [Archins, writingSystemUsedForLanguage, Cyrillic script]
  • A. writingSystemUsedIn chosen
    Indicates that a particular writing system is employed for written communication within a given language, region, or context.
  • B. writingSystemDevelopedFor
    Indicates that a particular writing system was created or adapted specifically to be used for a given language, community, or purpose.
  • C. writingSystem
    Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
  • D. writingSystemStandardized
    Indicates that a writing system has been formally codified and regulated according to an accepted standard or set of rules.
  • E. hasOfficialWritingSystem
    Indicates that an entity (typically a language) is associated with a formally recognized and standardized writing system used for official or standard purposes.
  • 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_69f0a7a180e48190ae775e40047dbcb5 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f674e06c9481909ed0ea736408f0d7 completed May 2, 2026, 10:04 p.m.
PD Predicate disambiguation batch_69f673c4abec8190bc2379e66f4af0a9 completed May 2, 2026, 9:59 p.m.
Created at: April 28, 2026, 3:21 p.m.