Triple

T15944802
Position Surface form Disambiguated ID Type / Status
Subject North Omotic E386656 entity
Predicate hasLanguage P15 FINISHED
Object Sheko language
The Sheko language is an Afroasiatic Omotic language spoken primarily by the Sheko people in southwestern Ethiopia.
 E1185206 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: Sheko language | Statement: [North Omotic, hasLanguage, Sheko language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sheko language
Context triple: [North Omotic, hasLanguage, Sheko language]
  • A. Makhuwa-Saka language
    The Makhuwa-Saka language is a Bantu language variety of the Makhuwa cluster spoken primarily in northern Mozambique.
  • B. Teke-Ngungwel language
    The Teke-Ngungwel language is a Bantu language spoken by the Teke people in Central Africa, particularly in parts of the Republic of the Congo and neighboring regions.
  • C. Kalanga language
    The Kalanga language is a Bantu language spoken primarily by the Kalanga people in parts of Botswana and southwestern Zimbabwe.
  • D. Tembe language
    The Tembe language is an indigenous Tupi-Guarani language spoken by the Tembé people of northern Brazil.
  • E. Makhuwa-Enahara language
    The Makhuwa-Enahara language is a Bantu language spoken primarily in northern Mozambique as one of the varieties of the broader Makhuwa language cluster.
  • 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: Sheko language
Triple: [North Omotic, hasLanguage, Sheko language]
Generated description
The Sheko language is an Afroasiatic Omotic language spoken primarily by the Sheko people in southwestern Ethiopia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sheko language
Target entity description: The Sheko language is an Afroasiatic Omotic language spoken primarily by the Sheko people in southwestern Ethiopia.
  • A. Makhuwa-Saka language
    The Makhuwa-Saka language is a Bantu language variety of the Makhuwa cluster spoken primarily in northern Mozambique.
  • B. Teke-Ngungwel language
    The Teke-Ngungwel language is a Bantu language spoken by the Teke people in Central Africa, particularly in parts of the Republic of the Congo and neighboring regions.
  • C. Kalanga language
    The Kalanga language is a Bantu language spoken primarily by the Kalanga people in parts of Botswana and southwestern Zimbabwe.
  • D. Tembe language
    The Tembe language is an indigenous Tupi-Guarani language spoken by the Tembé people of northern Brazil.
  • E. Makhuwa-Enahara language
    The Makhuwa-Enahara language is a Bantu language spoken primarily in northern Mozambique as one of the varieties of the broader Makhuwa language cluster.
  • 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_69d86da882448190a82ea962fe343b79 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156d016588190ae368197dfa7d43a completed April 16, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5beabbc8190977f14c1b3ccdf29 completed May 9, 2026, 10:31 p.m.
NEDg Description generation batch_69ffb677927c8190bd45e7bae5fcf1ed completed May 9, 2026, 10:34 p.m.
NED2 Entity disambiguation (via description) batch_69ffb7468fb88190a56cf1df5bd20f63 completed May 9, 2026, 10:37 p.m.
Created at: April 10, 2026, 4:53 a.m.