Triple

T5755444
Position Surface form Disambiguated ID Type / Status
Subject Zhuang language E126954 entity
Predicate closelyRelatedTo P37 FINISHED
Object Bouyei language E257937 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: Bouyei language | Statement: [Zhuang language, closelyRelatedTo, Bouyei language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bouyei language
Context triple: [Zhuang language, closelyRelatedTo, Bouyei language]
  • A. Bouyei language chosen
    The Bouyei language is a Tai–Kadai language spoken primarily by the Bouyei ethnic group in southern China, especially in Guizhou Province.
  • B. Banda-Bogbo language
    The Banda-Bogbo language is a Central Sudanic language spoken by the Banda people in parts of the Central African Republic.
  • C. Akawaio language
    The Akawaio language is an indigenous Cariban language spoken by the Akawaio people of Guyana, Venezuela, and Brazil.
  • D. Baniwa language
    Baniwa is an Arawakan Indigenous language spoken primarily along the Rio Negro in northwestern Brazil, as well as in parts of Colombia and Venezuela.
  • E. Bambam language
    The Bambam language is an Austronesian language spoken in parts of South Sulawesi, Indonesia, known for its place within the region’s diverse indigenous linguistic landscape.
  • 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_69c00832aedc81909899801b141fa3b4 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02906848c8190bf7b0d62f57c27fa completed March 22, 2026, 5:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e47c1788190b5883df385475237 completed March 22, 2026, 11:41 p.m.
Created at: March 22, 2026, 3:49 p.m.