Triple

T22097835
Position Surface form Disambiguated ID Type / Status
Subject Hua E546083 entity
Predicate romanization P2508 FINISHED
Object Hua NE NERFINISHED

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: Hua | Statement: [Hua, romanization, Hua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hua
Context triple: [Hua, romanization, Hua]
  • A. Hua chosen
    Hua is a Chinese given name commonly used for both males and females, often associated with meanings like "flower" or "China."
  • B. Hui
    The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
  • C. Hui
    Hui is a Chinese given name commonly used for both males and females, often associated with meanings such as "wisdom" or "favor" depending on the characters used.
  • D. Huan
    Huan is a given name most notably associated with the contemporary Chinese artist Zhang Huan, known for his performance and conceptual art.
  • E. Huayu
    Huayu is a term used primarily in Singapore, Malaysia, and other overseas Chinese communities to refer to the standardized form of Mandarin Chinese used in education and media.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128ea00d48190b020aba80dcdbec9 completed April 28, 2026, 9:38 p.m.
Created at: April 16, 2026, 8:30 p.m.