Triple

T13510682
Position Surface form Disambiguated ID Type / Status
Subject Wenzhounese E321130 entity
Predicate languageGroup P3349 FINISHED
Object Wu E66200 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: Wu | Statement: [Wenzhounese, languageGroup, Wu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wu
Context triple: [Wenzhounese, languageGroup, Wu]
  • A. Wu chosen
    Wu is a common Chinese surname borne by many notable individuals across politics, academia, entertainment, and sports.
  • B. Zhu
    Zhu is a common Chinese surname borne by many notable historical and contemporary figures in China.
  • C. Zhou
    Zhou is a common Chinese surname borne by many notable figures in Chinese history and politics.
  • D. Wu Yi
    Wu Yi is a Chinese politician who served as Vice Premier of the State Council and was widely known for her leadership in economic policy and public health crises such as the SARS outbreak.
  • E. Wu Xiang
    Wu Xiang was a Ming dynasty military official and nobleman best known as the father of the powerful general and later Qing collaborator Wu Sangui.
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf86a6208190be8c18f7a0158f23 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76ba835f08190bdc21de864e0fcc8 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:43 p.m.