Triple

T397283
Position Surface form Disambiguated ID Type / Status
Subject Kazakhstan E9209 entity
Predicate majorCity P316 FINISHED
Object Karaganda
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
 E52322 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: Karaganda | Statement: [Kazakhstan, majorCity, Karaganda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Karaganda
Context triple: [Kazakhstan, majorCity, Karaganda]
  • A. Almaty
    Almaty is the largest city and main commercial and cultural center of Kazakhstan, located in the country’s mountainous southeast.
  • B. Shymkent
    Shymkent is one of the largest and most populous cities in southern Kazakhstan, serving as a key industrial, commercial, and cultural center of the region.
  • C. Kazan
    Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
  • D. Astana
    Astana is the planned, modernist capital city of Kazakhstan, known for its futuristic architecture and rapid development since the late 20th century.
  • E. Derbent
    Derbent is an ancient fortified city in the Republic of Dagestan, Russia, strategically located on the Caspian Sea and known as one of the oldest continuously inhabited cities in the region.
  • 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: Karaganda
Triple: [Kazakhstan, majorCity, Karaganda]
Generated description
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Karaganda
Target entity description: Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
  • A. Almaty
    Almaty is the largest city and main commercial and cultural center of Kazakhstan, located in the country’s mountainous southeast.
  • B. Shymkent
    Shymkent is one of the largest and most populous cities in southern Kazakhstan, serving as a key industrial, commercial, and cultural center of the region.
  • C. Kazan
    Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
  • D. Astana
    Astana is the planned, modernist capital city of Kazakhstan, known for its futuristic architecture and rapid development since the late 20th century.
  • E. Derbent
    Derbent is an ancient fortified city in the Republic of Dagestan, Russia, strategically located on the Caspian Sea and known as one of the oldest continuously inhabited cities in the region.
  • 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_69a2e8004cb88190b92ed1add6abf41a completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ec8bcf708190b62e15806159ceb1 completed Feb. 28, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a41b4695288190b4a7e67b6a112ca6 completed March 1, 2026, 10:56 a.m.
NEDg Description generation batch_69a41ef33c3c81909c8c9ce2964748ee completed March 1, 2026, 11:11 a.m.
NED2 Entity disambiguation (via description) batch_69a4206a7ef8819086cf8c02f098551e completed March 1, 2026, 11:18 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.