Triple

T499721
Position Surface form Disambiguated ID Type / Status
Subject Ruqʿah script E10373 entity
Predicate usageContext P5018 FINISHED
Object school handwriting in many Arab countries 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: school handwriting in many Arab countries | Statement: [Ruqʿah script, usageContext, school handwriting in many Arab countries]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usageContext
Context triple: [Ruqʿah script, usageContext, school handwriting in many Arab countries]
  • A. usageType
    Indicates the specific manner, purpose, or context in which something is used or intended to be used.
  • B. contextOf
    Indicates that one entity provides the situational, informational, or environmental background within which another entity exists, occurs, or is interpreted.
  • C. context
    Indicates that one entity provides the surrounding circumstances, setting, or background within which another entity, event, or statement occurs or is interpreted.
  • D. scopeOfUse chosen
    Indicates the range, context, or conditions under which something is intended, allowed, or applicable to be used.
  • E. usagePattern
    Indicates how something is typically used or the recurring manner in which it is employed or consumed.
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f13096248190a622a58dcf540b00 completed Feb. 28, 2026, 1:44 p.m.
PD Predicate disambiguation batch_69a2edfa87cc8190a77c726a5a55b7d9 completed Feb. 28, 2026, 1:30 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.