Triple

T23690997
Position Surface form Disambiguated ID Type / Status
Subject Jajinci E585295 entity
Predicate writingSystemOfToponym P454 FINISHED
Object Cyrillic and Latin scripts 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 and Latin scripts | Statement: [Jajinci, writingSystemOfToponym, Cyrillic and Latin scripts]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: writingSystemOfToponym
Context triple: [Jajinci, writingSystemOfToponym, Cyrillic and Latin scripts]
  • A. writingSystemStandardized
    Indicates that a writing system has been formally codified and regulated according to an accepted standard or set of rules.
  • B. writingSystem chosen
    Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
  • C. toponymsMayDifferInScript
    Indicates that two toponyms refer to the same place but are written using different writing systems or scripts.
  • D. writingSystemUsedIn
    Indicates that a particular writing system is employed for written communication within a given language, region, or context.
  • E. writingSystemDevelopedFor
    Indicates that a particular writing system was created or adapted specifically to be used for a given language, community, or purpose.
  • 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_69e249037ce0819088b149608e98f685 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b5c27af481908c6dbe59c71de82a completed April 29, 2026, 7:39 a.m.
PD Predicate disambiguation batch_69f155d5265881908e43a9696b6a6d0f completed April 29, 2026, 12:50 a.m.
Created at: April 17, 2026, 6:52 p.m.