Triple

T11012483
Position Surface form Disambiguated ID Type / Status
Subject Kam language E260275 entity
Predicate subfamily P4180 FINISHED
Object Kam–Sui E893917 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: Kam–Sui | Statement: [Kam language, subfamily, Kam–Sui]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kam–Sui
Context triple: [Kam language, subfamily, Kam–Sui]
  • A. Kam–Sui chosen
    Kam–Sui is a branch of the Kra–Dai language family comprising several closely related languages spoken primarily by ethnic minority groups in southern China and neighboring regions.
  • B. Xintai
    Xintai is a county-level city in Shandong Province, China, administered by the prefecture-level city of Tai'an.
  • C. Taishi
    Taishi was the first era name used by Emperor Wu of the Western Han dynasty, marking an important early phase of his long and influential reign in ancient China.
  • D. Taishi
    Taishi is a town in Osaka Prefecture, Japan, known for its historical sites and traditional rural character.
  • E. Kwang-chou
    Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7978a57a881909b4ceae0ebe21b78 completed April 9, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69e374ac78348190a8c0a5a7a736b24b completed April 18, 2026, 12:10 p.m.
Created at: April 8, 2026, 9:25 p.m.