Triple

T13843478
Position Surface form Disambiguated ID Type / Status
Subject Kasese E332728 entity
Predicate languageUsed P238 FINISHED
Object Runyakitara
Runyakitara is a standardized Bantu language of western Uganda that unifies several closely related Runyoro, Rutooro, Runyankore, and Rukiga varieties.
 E695723 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: Runyakitara | Statement: [Kasese, languageUsed, Runyakitara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runyakitara
Context triple: [Kasese, languageUsed, Runyakitara]
  • A. Runyoro
    Runyoro is a Bantu language spoken primarily by the Banyoro people in western Uganda.
  • B. Kitwe
    Kitwe is a major mining and industrial city in Zambia’s Copperbelt Province, known as one of the country’s largest urban and economic centers.
  • C. Nyamwezi language
    The Nyamwezi language is a Bantu language spoken primarily by the Nyamwezi people of western-central Tanzania.
  • D. Gikuyu
    Gikuyu is an alternative name for the Kikuyu, the largest ethnic group in Kenya known for their Bantu language and significant cultural and political influence in the country.
  • E. Nyanja
    Nyanja is a major Bantu language spoken primarily in Malawi, Zambia, Mozambique, and Zimbabwe, known for serving as a lingua franca in parts of southern Africa.
  • 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: Runyakitara
Triple: [Kasese, languageUsed, Runyakitara]
Generated description
Runyakitara is a standardized Bantu language of western Uganda that unifies several closely related Runyoro, Rutooro, Runyankore, and Rukiga varieties.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Runyakitara
Target entity description: Runyakitara is a standardized Bantu language of western Uganda that unifies several closely related Runyoro, Rutooro, Runyankore, and Rukiga varieties.
  • A. Runyoro chosen
    Runyoro is a Bantu language spoken primarily by the Banyoro people in western Uganda.
  • B. Kitwe
    Kitwe is a major mining and industrial city in Zambia’s Copperbelt Province, known as one of the country’s largest urban and economic centers.
  • C. Nyamwezi language
    The Nyamwezi language is a Bantu language spoken primarily by the Nyamwezi people of western-central Tanzania.
  • D. Gikuyu
    Gikuyu is an alternative name for the Kikuyu, the largest ethnic group in Kenya known for their Bantu language and significant cultural and political influence in the country.
  • E. Nyanja
    Nyanja is a major Bantu language spoken primarily in Malawi, Zambia, Mozambique, and Zimbabwe, known for serving as a lingua franca in parts of southern Africa.
  • F. None of above.

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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02afce788190a74dce4e6a3569fa completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8f87c188190b90faf7678cb9ad4 completed May 3, 2026, 9:07 p.m.
NEDg Description generation batch_69f7b9da1f848190a0c7e8d8a2b0954d completed May 3, 2026, 9:10 p.m.
NED2 Entity disambiguation (via description) batch_69f7bbf47c888190be32a4105903120a completed May 3, 2026, 9:19 p.m.
Created at: April 9, 2026, 10:13 p.m.