Triple

T453290
Position Surface form Disambiguated ID Type / Status
Subject Standard Chinese E7177 entity
Predicate basedOn P98 FINISHED
Object Mandarin Chinese E35123 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: Mandarin Chinese | Statement: [Standard Chinese, basedOn, Mandarin Chinese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mandarin Chinese
Context triple: [Standard Chinese, basedOn, Mandarin Chinese]
  • A. Standard Chinese
    Standard Chinese is the official standardized form of the Chinese language, based primarily on the Beijing dialect of Mandarin and used as the national lingua franca of China.
  • B. Teochew
    Teochew is a Southern Min Chinese dialect originating from the Chaoshan region of Guangdong, widely spoken in overseas Chinese communities across Southeast Asia.
  • C. Cantonese
    Cantonese is a major Chinese language variety spoken primarily in Guangdong province, Hong Kong, Macau, and among overseas Chinese communities worldwide.
  • D. Southwestern Mandarin chosen
    Southwestern Mandarin is a major branch of Mandarin Chinese spoken across much of southwestern China, characterized by distinct phonological features and regional variations.
  • E. Xiang Chinese
    Xiang Chinese is a major Sinitic language variety spoken primarily in Hunan province and surrounding regions in south-central China.
  • 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_69a2e7e4676c81909ea0dbdecac0687c completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ef866e848190a5b700250ec56256 completed Feb. 28, 2026, 1:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69a44cbc3b708190ab27ce4d323472b9 completed March 1, 2026, 2:27 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.