Triple

T7790040
Position Surface form Disambiguated ID Type / Status
Subject Ganxian Hakka E187352 entity
Predicate languageBranch P1967 FINISHED
Object Hakka E34449 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: Hakka | Statement: [Ganxian Hakka, languageBranch, Hakka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hakka
Context triple: [Ganxian Hakka, languageBranch, Hakka]
  • A. Hakka chosen
    Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
  • B. Hokkien
    Hokkien is a Southern Min Chinese language variety widely spoken in Taiwan, Southeast Asia, and parts of southern China, known for its rich tonal system and distinct vocabulary from Mandarin.
  • C. Chōmin
    Chōmin was the pen name of Nakae Chōmin, a prominent Japanese political theorist, journalist, and early advocate of liberal democracy during the Meiji era.
  • D. Jiaoqu
    Jiaoqu is an urban district that forms part of the prefecture-level city of Tongling in Anhui Province, China.
  • E. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • 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_69ca82af2d2c8190963861f5e0b8bf21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cae7ea13f08190a60c5f1863bce816 completed March 30, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69caf62c8568819090c058b0c55b7865 completed March 30, 2026, 10:16 p.m.
Created at: March 30, 2026, 4:25 p.m.