Triple

T5932869
Position Surface form Disambiguated ID Type / Status
Subject Mappila Muslims E131976 entity
Predicate usesReligiousTextLanguage P1187 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: [Mappila Muslims, usesReligiousTextLanguage, Arabic]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesReligiousTextLanguage
Context triple: [Mappila Muslims, usesReligiousTextLanguage, Arabic]
  • A. religiousTextLanguageOf
    Indicates that a particular language is the language in which a given religious text is written or primarily expressed.
  • B. usedForReligiousLanguage
    Indicates that something is employed specifically in the context of religious language, such as for expressing, communicating, or performing religious beliefs, practices, or rituals.
  • C. usedForReligiousTexts
    Indicates that something is used in the creation, preservation, or practice of religious texts or scriptures.
  • D. hasLanguageOfScripture chosen
    Indicates that an entity’s scriptural or sacred texts are written or expressed in a specified language.
  • E. isAssociatedWithReligiousText
    Indicates a relationship where an entity is connected or linked in some way to a religious text, such as being based on, derived from, or directly related to it.
  • 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_69c0085b75e88190a632f9691f9da48b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03f26f51881908cc253fe5775a1fc completed March 22, 2026, 7:12 p.m.
PD Predicate disambiguation batch_69c03355caf08190b960563a1aed23f9 completed March 22, 2026, 6:22 p.m.
Created at: March 22, 2026, 4 p.m.