Triple

T273838
Position Surface form Disambiguated ID Type / Status
Subject Guangzhou E5203 entity
Predicate languageUsed P238 FINISHED
Object Cantonese E25452 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: Cantonese | Statement: [Guangzhou, languageUsed, Cantonese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cantonese
Context triple: [Guangzhou, languageUsed, Cantonese]
  • A. Cantonese chosen
    Cantonese is a major Chinese language variety spoken primarily in Guangdong province, Hong Kong, Macau, and among overseas Chinese communities worldwide.
  • B. Southwestern Mandarin
    Southwestern Mandarin is a major branch of Mandarin Chinese spoken across much of southwestern China, characterized by distinct phonological features and regional variations.
  • C. 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.
  • D. Hakka
    Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
  • E. Formosan languages
    Formosan languages are a group of indigenous Austronesian languages spoken primarily by the native peoples of Taiwan and considered crucial for understanding the early diversification of the Austronesian language family.
  • 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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25dd0a99c819089968a5400c58c5f completed Feb. 28, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a38f5471d88190bcb8b9117575555b completed March 1, 2026, 12:59 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.