Triple

T1745533
Position Surface form Disambiguated ID Type / Status
Subject Arabic alphabet E38326 entity
Predicate hasTransliterationSystems P23170 FINISHED
Object multiple Latin-based systems 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: multiple Latin-based systems | Statement: [Arabic alphabet, hasTransliterationSystems, multiple Latin-based systems]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTransliterationSystems
Context triple: [Arabic alphabet, hasTransliterationSystems, multiple Latin-based systems]
  • A. alternativeTransliteration
    Indicates that one written form represents an alternative way of transliterating the same original text or name into another script or orthography.
  • B. hasRomanizationOf
    Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
  • C. hasRomanizationStandard chosen
    Indicates that an entity’s romanized form follows a specified romanization standard or system.
  • D. writingSystemFeatures
    Indicates the specific structural or functional characteristics that define how a particular writing system represents language.
  • E. hasSyllabary
    Indicates that one entity possesses or is associated with a specific syllabary writing system used to represent its language or notation.
  • 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_69a8862b01a48190ab47209063af82d9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69ab630e7d008190a8c673665d9672bb completed March 6, 2026, 11:28 p.m.
PD Predicate disambiguation batch_69aa61c5a18481909bc49e0c54d64314 completed March 6, 2026, 5:10 a.m.
Created at: March 4, 2026, 7:31 p.m.