Triple

T10094179
Position Surface form Disambiguated ID Type / Status
Subject Emblem of Algeria E215819 entity
Predicate writingSystemOfInscription P26603 FINISHED
Object Arabic alphabet 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: Arabic alphabet | Statement: [Emblem of Algeria, writingSystemOfInscription, Arabic alphabet]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: writingSystemOfInscription
Context triple: [Emblem of Algeria, writingSystemOfInscription, Arabic alphabet]
  • A. writingSystem
    Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
  • B. writingSystemUsedIn chosen
    Indicates that a particular writing system is employed for written communication within a given language, region, or context.
  • C. writingSystemDevelopedFor
    Indicates that a particular writing system was created or adapted specifically to be used for a given language, community, or purpose.
  • D. writingSystemDeciphered
    Indicates that the writing system used by an entity has been successfully interpreted and its symbols and structure are understood.
  • E. writingSystemClass
    Indicates that one entity is classified as a type or category of writing system to which the other entity belongs.
  • 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_69ca83a4947c8190823a7495dc5d96ed completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd05da3688190b7a1ac8a58e5488f completed April 2, 2026, 2:11 a.m.
PD Predicate disambiguation batch_69cd4b9b853c8190a2af993ce9b21309 completed April 1, 2026, 4:45 p.m.
Created at: March 30, 2026, 9:01 p.m.