Triple

T38154782
Position Surface form Disambiguated ID Type / Status
Subject Sharq al-Andalus E952854 entity
Predicate usedReligiousLanguage P33427 FINISHED
Object Arabic 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 | Statement: [Sharq al-Andalus, usedReligiousLanguage, Arabic]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usedReligiousLanguage
Context triple: [Sharq al-Andalus, usedReligiousLanguage, Arabic]
  • A. usedForReligiousLanguage chosen
    Indicates that something is employed specifically in the context of religious language, such as for expressing, communicating, or performing religious beliefs, practices, or rituals.
  • B. positionOnReligiousLanguage
    Indicates a stance or viewpoint someone holds regarding how religious language should be understood, interpreted, or used.
  • C. languageOfReligion
    Indicates the language in which a particular religion is traditionally expressed, practiced, or documented.
  • D. usesReligiousRhetoric
    Indicates that one entity employs religious language, themes, or references as part of its communication, argumentation, or persuasive efforts toward another entity or audience.
  • E. usedReligionFor
    Indicates that an entity employed religion as a means or tool to achieve some purpose, goal, or effect.
  • 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_69f76f0a67f4819080c492f61d688fcc completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fcc42cbac48190b8d3e4c9ce140838 completed May 7, 2026, 4:56 p.m.
PD Predicate disambiguation batch_69fcb0fc69c88190800453eb57a7e62c completed May 7, 2026, 3:34 p.m.
Created at: May 3, 2026, 4:21 p.m.