Triple

T22526265
Position Surface form Disambiguated ID Type / Status
Subject زكريا عزمي E556911 entity
Predicate اللغة المستخدمة في الحياة العامة P72909 FINISHED
Object العربية المصرية 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: العربية المصرية | Statement: [زكريا عزمي, اللغة المستخدمة في الحياة العامة, العربية المصرية]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: اللغة المستخدمة في الحياة العامة
Context triple: [زكريا عزمي, اللغة المستخدمة في الحياة العامة, العربية المصرية]
  • A. typicalLanguageUse chosen
    Indicates that one entity is the language most commonly or habitually used by another entity in ordinary communication or contexts.
  • B. officialLanguageUse
    Indicates that a particular language is formally designated and used by an authority (such as a government or institution) for official communication, documentation, or functions.
  • C. usedInLanguage
    Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
  • D. overarchingLanguage
    Indicates that one language serves as the primary or dominant linguistic framework governing or unifying other languages or language varieties in a given context.
  • E. linguisticUsage
    Indicates how a linguistic form, expression, or construction is used in language, such as its typical context, function, or register.
  • 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_69e11e5657e881909f16ca58352c50da completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ed352b48190a96ef2896f2978cd completed April 29, 2026, 1:28 a.m.
PD Predicate disambiguation batch_69ee625e3b408190a60c759fb0b28fe2 completed April 26, 2026, 7:07 p.m.
Created at: April 16, 2026, 8:51 p.m.