Triple

T7570336
Position Surface form Disambiguated ID Type / Status
Subject Mashonaland West Province E179222 entity
Predicate hasTown P847 FINISHED
Object Kadoma
Kadoma is a city in central Zimbabwe known for its gold mining and agricultural activities.
 E672882 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: Kadoma | Statement: [Mashonaland West Province, hasTown, Kadoma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kadoma
Context triple: [Mashonaland West Province, hasTown, Kadoma]
  • A. Kadoma
    Kadoma is a city in Osaka Prefecture, Japan, known as a residential and commercial suburb within the Osaka metropolitan area.
  • B. Omuta
    Omuta is an industrial city in southern Fukuoka Prefecture, Japan, historically known for its coal mining and chemical industries.
  • C. Mathare
    Mathare is a densely populated informal settlement and neighborhood in Nairobi, Kenya, known for its extensive slums and socio-economic challenges.
  • D. Oshakati
    Oshakati is a major northern Namibian town that serves as an important commercial and administrative hub.
  • E. Kalangoya
    Kalangoya is an alternative name for the Kalanguya language, an Austronesian language spoken by indigenous communities in the northern Philippines.
  • 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: Kadoma
Triple: [Mashonaland West Province, hasTown, Kadoma]
Generated description
Kadoma is a city in central Zimbabwe known for its gold mining and agricultural activities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kadoma
Target entity description: Kadoma is a city in central Zimbabwe known for its gold mining and agricultural activities.
  • A. Kadoma
    Kadoma is a city in Osaka Prefecture, Japan, known as a residential and commercial suburb within the Osaka metropolitan area.
  • B. Omuta
    Omuta is an industrial city in southern Fukuoka Prefecture, Japan, historically known for its coal mining and chemical industries.
  • C. Mathare
    Mathare is a densely populated informal settlement and neighborhood in Nairobi, Kenya, known for its extensive slums and socio-economic challenges.
  • D. Oshakati
    Oshakati is a major northern Namibian town that serves as an important commercial and administrative hub.
  • E. Kalangoya
    Kalangoya is an alternative name for the Kalanguya language, an Austronesian language spoken by indigenous communities in the northern Philippines.
  • 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_69c69f316e50819081a271c85c06f918 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f920540c8190817712db5aa3eeff completed March 27, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856e475348190a7c1e9872b513899 completed March 28, 2026, 10:32 p.m.
NEDg Description generation batch_69c857738e6881908abfce108d71efc0 completed March 28, 2026, 10:34 p.m.
NED2 Entity disambiguation (via description) batch_69c857e4a0408190b395389c6221e259 completed March 28, 2026, 10:36 p.m.
Created at: March 27, 2026, 3:51 p.m.