Triple

T16584107
Position Surface form Disambiguated ID Type / Status
Subject Suzhounese E402908 entity
Predicate subgroupOf P10 FINISHED
Object Taihu Wu E404458 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: Taihu Wu | Statement: [Suzhounese, subgroupOf, Taihu Wu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taihu Wu
Context triple: [Suzhounese, subgroupOf, Taihu Wu]
  • A. Taihu Wu chosen
    Taihu Wu is a major subgroup of the Wu varieties of Chinese, spoken in and around the Yangtze River Delta including cities such as Shanghai, Suzhou, and Hangzhou.
  • B. Pai Mei
    Pai Mei is a legendary, ruthless martial arts master in Quentin Tarantino’s Kill Bill saga, known for his brutal training methods and near-mythic fighting skills.
  • C. Wu Ta-You
    Wu Ta-You was a prominent Chinese theoretical physicist often regarded as the father of modern Chinese physics.
  • D. Wu
    Wu is a common Chinese surname borne by many notable individuals across politics, academia, entertainment, and sports.
  • E. Oujiang Wu
    Oujiang Wu is a subgroup of the Wu branch of Chinese, spoken primarily in and around Wenzhou in China’s Zhejiang province and known for its distinct phonology and relative unintelligibility to speakers of other Chinese varieties.
  • 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35999f80c8190852fd4137bc45a80 completed April 18, 2026, 10:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ef2d6048190954144ab848760ec completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:16 a.m.