Triple

T9049492
Position Surface form Disambiguated ID Type / Status
Subject Hoa E216846 entity
Predicate language P15 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: [Hoa, language, Hakka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hakka
Context triple: [Hoa, language, 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. Raoping Hakka
    Raoping Hakka is a major regional variety of the Hakka Chinese language, traditionally spoken in the Raoping area and influential among Hakka communities in Taiwan.
  • D. Hànshū
    Hànshū is the standard pinyin title of the "Book of Han," a major Chinese historical text documenting the history of the Western Han dynasty.
  • E. Hakka language
    The Hakka language is a Sinitic language spoken primarily by the Hakka people across southern China and the global Chinese diaspora, known for its distinct phonology and rich folk song and literary traditions.
  • 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_69ca83d362e88190ae44b4e4dc194209 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc6b52cc1881909fb011d9a8af2e18 completed April 1, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffdbd54848190ba79d873321f4fc9 completed April 3, 2026, 5:49 p.m.
Created at: March 30, 2026, 7:10 p.m.