Triple

T10586579
Position Surface form Disambiguated ID Type / Status
Subject Toposa language E249869 entity
Predicate hasDialect P4251 FINISHED
Object Kidepo Toposa
Kidepo Toposa is a regional dialect of the Toposa language spoken by Toposa communities in the Kidepo area of South Sudan.
E872571 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: Kidepo Toposa | Statement: [Toposa language, hasDialect, Kidepo Toposa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kidepo Toposa
Context triple: [Toposa language, hasDialect, Kidepo Toposa]
  • A. Nuba
    Nuba is a Palestinian village located in the Hebron Governorate in the southern West Bank.
  • B. Zande
    Zande is a Central African language spoken primarily by the Azande people across parts of South Sudan, the Central African Republic, and the Democratic Republic of the Congo.
  • C. Ndau
    Ndau is a Southern Bantu language spoken primarily in central Mozambique and eastern Zimbabwe, closely related to Shona.
  • D. Inibaloi
    Inibaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in Benguet province on Luzon.
  • E. Nyakyusa
    The Nyakyusa are a Bantu-speaking ethnic group primarily inhabiting the northern shores of Lake Malawi in southern Tanzania, known for their intensive agriculture and distinctive age-village social system.
  • 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: Kidepo Toposa
Triple: [Toposa language, hasDialect, Kidepo Toposa]
Generated description
Kidepo Toposa is a regional dialect of the Toposa language spoken by Toposa communities in the Kidepo area of South Sudan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kidepo Toposa
Target entity description: Kidepo Toposa is a regional dialect of the Toposa language spoken by Toposa communities in the Kidepo area of South Sudan.
  • A. Nuba
    Nuba is a Palestinian village located in the Hebron Governorate in the southern West Bank.
  • B. Zande
    Zande is a Central African language spoken primarily by the Azande people across parts of South Sudan, the Central African Republic, and the Democratic Republic of the Congo.
  • C. Ndau
    Ndau is a Southern Bantu language spoken primarily in central Mozambique and eastern Zimbabwe, closely related to Shona.
  • D. Inibaloi
    Inibaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in Benguet province on Luzon.
  • E. Nyakyusa
    The Nyakyusa are a Bantu-speaking ethnic group primarily inhabiting the northern shores of Lake Malawi in southern Tanzania, known for their intensive agriculture and distinctive age-village social system.
  • 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_69d381c9d3d48190a29ee491e1696a0e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5276b0ae48190b2935230363239e0 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b8b1b708190865e428128f98720 completed April 10, 2026, 7:12 p.m.
NEDg Description generation batch_69d94d68f39c8190bc7ea90237a5bf5f completed April 10, 2026, 7:20 p.m.
NED2 Entity disambiguation (via description) batch_69d9522d68b88190a63acb6d657168b4 completed April 10, 2026, 7:40 p.m.
Created at: April 6, 2026, 12:39 p.m.