Triple

T10586621
Position Surface form Disambiguated ID Type / Status
Subject Kadu languages E249870 entity
Predicate hasMemberLanguage P7390 FINISHED
Object Keiga language
The Keiga language is a Kadu (Kadugli) language spoken by the Keiga people in the Nuba Mountains region of Sudan.
 E876949 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: Keiga language | Statement: [Kadu languages, hasMemberLanguage, Keiga language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Keiga language
Context triple: [Kadu languages, hasMemberLanguage, Keiga language]
  • A. Kiga language
    The Kiga language is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda.
  • B. Kaera language
    The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
  • C. Chimariko language
    The Chimariko language is an extinct Native American language once spoken in northwestern California, often classified within the proposed Hokan language family.
  • D. Teke-Kega language
    The Teke-Kega language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo and surrounding regions.
  • E. Karkar-Yuri language
    Karkar-Yuri is a Papuan language of Papua New Guinea, spoken by the Karkar and Yuri peoples in the Sepik 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: Keiga language
Triple: [Kadu languages, hasMemberLanguage, Keiga language]
Generated description
The Keiga language is a Kadu (Kadugli) language spoken by the Keiga people in the Nuba Mountains region of Sudan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Keiga language
Target entity description: The Keiga language is a Kadu (Kadugli) language spoken by the Keiga people in the Nuba Mountains region of Sudan.
  • A. Kiga language
    The Kiga language is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda.
  • B. Kaera language
    The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
  • C. Chimariko language
    The Chimariko language is an extinct Native American language once spoken in northwestern California, often classified within the proposed Hokan language family.
  • D. Teke-Kega language
    The Teke-Kega language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo and surrounding regions.
  • E. Karkar-Yuri language
    Karkar-Yuri is a Papuan language of Papua New Guinea, spoken by the Karkar and Yuri peoples in the Sepik 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_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_69d97a1bba1c8190af5a078f40f3bc0a completed April 10, 2026, 10:30 p.m.
NEDg Description generation batch_69d97c7bc87481908d50eb6f294170eb completed April 10, 2026, 10:40 p.m.
NED2 Entity disambiguation (via description) batch_69d97e015b088190a97822675eecaa5a completed April 10, 2026, 10:47 p.m.
Created at: April 6, 2026, 12:39 p.m.