Triple

T3015311
Position Surface form Disambiguated ID Type / Status
Subject Wu Chinese E82322 entity
Predicate hasMajorVariety P455 FINISHED
Object Suzhounese E155949 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: Suzhounese | Statement: [Wu Chinese, hasMajorVariety, Suzhounese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suzhounese
Context triple: [Wu Chinese, hasMajorVariety, Suzhounese]
  • A. Teochew
    Teochew is a Southern Min Chinese dialect originating from the Chaoshan region of Guangdong, widely spoken in overseas Chinese communities across Southeast Asia.
  • B. Shanghainese chosen
    Shanghainese is a Wu Chinese dialect spoken primarily in Shanghai and its surrounding region, known for its distinct phonology and limited mutual intelligibility with Mandarin.
  • C. Heyuan Hakka
    Heyuan Hakka is a regional variety of the Hakka Chinese language spoken primarily in and around Heyuan in Guangdong Province, China.
  • D. Siwu language
    The Siwu language is a Niger-Congo language spoken primarily in the Volta Region of Ghana by the Mawu people.
  • E. Wuhua Hakka
    Wuhua Hakka is a regional variety of the Hakka Chinese language spoken primarily in Wuhua County, Guangdong, known for its distinctive phonological and lexical features.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a6b37288190a6965d183ca4b08b completed March 8, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e6b78448190beb41460314278ec completed March 11, 2026, 8:57 a.m.
Created at: March 8, 2026, 3 p.m.