Triple

T5021448
Position Surface form Disambiguated ID Type / Status
Subject Kashubia E112858 entity
Predicate hasWritingSystemForLanguage P26603 FINISHED
Object Latin 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: Latin alphabet | Statement: [Kashubia, hasWritingSystemForLanguage, Latin alphabet]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasWritingSystemForLanguage
Context triple: [Kashubia, hasWritingSystemForLanguage, Latin alphabet]
  • A. hasWritingSystemForMajorLanguage
    Indicates that there exists a writing system used to represent a major language associated with the given entity.
  • B. writingSystem
    Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
  • C. writingSystemFeatures
    Indicates the specific structural or functional characteristics that define how a particular writing system represents language.
  • D. writingSystemUsedIn chosen
    Indicates that a particular writing system is employed for written communication within a given language, region, or context.
  • E. writingSystemFound
    Indicates that a particular writing system is present, attested, or used in association with a given entity (such as a language, region, or community).
  • 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_69bd4435c2f48190be593158cbfcf8a3 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73656edc8190b802ad38d9552b58 completed March 20, 2026, 4:18 p.m.
PD Predicate disambiguation batch_69bd714ecfe08190b5830cfc1c74fa17 completed March 20, 2026, 4:09 p.m.
Created at: March 20, 2026, 1:36 p.m.