Triple

T34780465
Position Surface form Disambiguated ID Type / Status
Subject Cartoon Junction E1002642 entity
Predicate languageAdditional P11734 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: [Cartoon Junction, languageAdditional, Arabic]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageAdditional
Context triple: [Cartoon Junction, languageAdditional, Arabic]
  • A. languageSpecifies
    Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
  • B. languageCategory
    Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
  • C. alternateLanguageName
    Indicates that an entity has an additional name or label in a different language from its primary or default name.
  • D. languageIndependence
    Indicates that a concept, method, or representation does not depend on any specific programming or natural language and can be applied uniformly across different languages.
  • E. languageProvision chosen
    Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
  • 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_69f76db30a108190bb57ca95b873e5bb completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_6a008ac37dc081908d360574912f40ec completed May 10, 2026, 1:40 p.m.
PD Predicate disambiguation batch_6a008a67d73881909855ab4cfca3c399 completed May 10, 2026, 1:38 p.m.
Created at: May 3, 2026, 3:59 p.m.