Triple

T22050249
Position Surface form Disambiguated ID Type / Status
Subject Nüshu E544863 entity
Predicate language P15 FINISHED
Object Xiang Chinese 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: Xiang Chinese | Statement: [Nüshu, language, Xiang Chinese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xiang Chinese
Context triple: [Nüshu, language, Xiang Chinese]
  • A. Xiang Chinese chosen
    Xiang Chinese is a major Sinitic language variety spoken primarily in Hunan province and surrounding regions in south-central China.
  • B. Yue Chinese
    Yue Chinese is a major branch of the Chinese language family, best known internationally through its prominent variety Cantonese spoken in southern China and among overseas Chinese communities.
  • C. Hanyu
    Hanyu is a Chinese given name shared by various individuals, including notable figures in fields such as acting, sports, and academia.
  • D. Wu Chinese
    Wu Chinese is a major Sinitic language group spoken primarily in Shanghai, southern Jiangsu, and Zhejiang, known for its rich tonal system and significant phonological differences from Mandarin.
  • E. Chin language
    Chin language refers to a group of closely related Tibeto-Burman languages spoken primarily in Chin State of western Myanmar and adjacent regions of India and Bangladesh.
  • 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_69e11e32445c8190ab97089b48a130bb completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128323fb08190b9592fd08a96cba0 completed April 28, 2026, 9:35 p.m.
Created at: April 16, 2026, 8:26 p.m.