Triple

T12653742
Position Surface form Disambiguated ID Type / Status
Subject Vai language E302228 entity
Predicate hasWritingSystem P454 FINISHED
Object Vai syllabary E643330 NE 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: Vai syllabary | Statement: [Vai language, hasWritingSystem, Vai syllabary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vai syllabary
Context triple: [Vai language, hasWritingSystem, Vai syllabary]
  • A. Vai syllabary chosen
    The Vai syllabary is an indigenous writing system from Liberia and Sierra Leone used to represent the Vai language of the Mande family.
  • B. Afaka syllabary
    The Afaka syllabary is an indigenous writing system developed in the early 20th century for the Ndyuka language of Suriname, notable as one of the few known scripts created by a Maroon community in the Americas.
  • C. Kana
    Kana is a settlement located within Pakistan’s Shangla District in the Khyber Pakhtunkhwa province.
  • D. Kana
    Kana is the Japanese syllabic writing system comprising hiragana and katakana, used to represent native words, grammatical elements, and foreign terms.
  • E. Katakana
    Katakana is one of the two main Japanese phonetic writing systems, primarily used for foreign words, onomatopoeia, emphasis, and technical or scientific terms.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96160730c81909e1aa3efb51bf159 completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6688104d48190939933b93b7e60cc completed May 2, 2026, 9:11 p.m.
Created at: April 9, 2026, 5:18 p.m.