Triple

T10920769
Position Surface form Disambiguated ID Type / Status
Subject Sui language E257938 entity
Predicate languageFamilyBranch P1967 FINISHED
Object Kam–Sui
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.
 E893917 NE FINISHED

How this triple was built (4 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: [Sui language, languageFamilyBranch, Kam–Sui]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kam–Sui
Context triple: [Sui language, languageFamilyBranch, Kam–Sui]
  • A. Xintai
    Xintai is a county-level city in Shandong Province, China, administered by the prefecture-level city of Tai'an.
  • B. 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.
  • C. Taishi
    Taishi is a town in Osaka Prefecture, Japan, known for its historical sites and traditional rural character.
  • D. 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.
  • E. Koung-Khi
    Koung-Khi is an administrative department located in the West Region of Cameroon.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kam–Sui
Triple: [Sui language, languageFamilyBranch, Kam–Sui]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kam–Sui
Target entity description: 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.
  • A. Xintai
    Xintai is a county-level city in Shandong Province, China, administered by the prefecture-level city of Tai'an.
  • B. 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.
  • C. Taishi
    Taishi is a town in Osaka Prefecture, Japan, known for its historical sites and traditional rural character.
  • D. 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.
  • E. Koung-Khi
    Koung-Khi is an administrative department located in the West Region of Cameroon.
  • F. None of above. chosen

Provenance (5 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d77082a1488190850a4409339c3e1e completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2171adbbc8190916a5463b6e5c186 completed April 17, 2026, 11:18 a.m.
NEDg Description generation batch_69e21d8a2e6881909b33cbe4ab919315 completed April 17, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_69e21eaa1e9881909f3b276e0ff0c511 completed April 17, 2026, 11:51 a.m.
Created at: April 8, 2026, 9:22 p.m.