Triple

T5755437
Position Surface form Disambiguated ID Type / Status
Subject Zhuang language E126954 entity
Predicate usesTraditionalScript P35394 FINISHED
Object Sawndip 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: Sawndip | Statement: [Zhuang language, usesTraditionalScript, Sawndip]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesTraditionalScript
Context triple: [Zhuang language, usesTraditionalScript, Sawndip]
  • A. isTraditional
    Indicates that something adheres to long-established customs, practices, or norms rather than modern or innovative ones.
  • B. hasTraditionalCharacter chosen
    Indicates that an entity is associated with or represented by a traditional (non-simplified or historically established) written character form.
  • C. usesColloquialCharacters
    Indicates that an expression, name, or text is written using informal, non-standard, or colloquial characters rather than formal or standard script.
  • D. hasTraditionalDialect
    Indicates that an entity possesses or is associated with a traditional form or variety of a language or dialect.
  • E. hasTraditionalName
    Indicates that an entity is associated with a name traditionally used or recognized for it, often rooted in long-standing cultural or historical practice.
  • 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_69c00832aedc81909899801b141fa3b4 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02906848c8190bf7b0d62f57c27fa completed March 22, 2026, 5:38 p.m.
PD Predicate disambiguation batch_69c021cc68648190bb86d049ebe80f12 completed March 22, 2026, 5:07 p.m.
Created at: March 22, 2026, 3:49 p.m.