Triple

T2531858
Position Surface form Disambiguated ID Type / Status
Subject Luganda E56177 entity
Predicate closelyRelatedTo P37 FINISHED
Object Lunyoro
Lunyoro is a Bantu language of Uganda, traditionally spoken by the Banyoro people in the western part of the country.
 E275006 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: Lunyoro | Statement: [Luganda, closelyRelatedTo, Lunyoro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lunyoro
Context triple: [Luganda, closelyRelatedTo, Lunyoro]
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Lusoga
    Lusoga is a Bantu language spoken primarily by the Basoga people in eastern Uganda.
  • C. Lumbu
    Lumbu is a Bantu ethnic group and language of Central Africa, primarily found in Gabon and the Republic of the Congo, culturally and linguistically related to neighboring Punu people.
  • D. Sanglechi
    Sanglechi is a lesser-known Eastern Iranian language spoken in parts of northeastern Afghanistan and adjacent regions.
  • E. Nyanda
    Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
  • 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: Lunyoro
Triple: [Luganda, closelyRelatedTo, Lunyoro]
Generated description
Lunyoro is a Bantu language of Uganda, traditionally spoken by the Banyoro people in the western part of the country.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lunyoro
Target entity description: Lunyoro is a Bantu language of Uganda, traditionally spoken by the Banyoro people in the western part of the country.
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Lusoga chosen
    Lusoga is a Bantu language spoken primarily by the Basoga people in eastern Uganda.
  • C. Lumbu
    Lumbu is a Bantu ethnic group and language of Central Africa, primarily found in Gabon and the Republic of the Congo, culturally and linguistically related to neighboring Punu people.
  • D. Sanglechi
    Sanglechi is a lesser-known Eastern Iranian language spoken in parts of northeastern Afghanistan and adjacent regions.
  • E. Nyanda
    Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
  • 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_69ab4a48e4f081908f1218d244608659 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd2781700819091ffc32244d9efe2 completed March 7, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5cf858cc81908d6a7ef5315119aa completed March 9, 2026, 11:51 p.m.
NEDg Description generation batch_69af5db1c290819099d88815ebe97c1b completed March 9, 2026, 11:54 p.m.
NED2 Entity disambiguation (via description) batch_69af5e2cd2588190bc24c3cdd350fa70 completed March 9, 2026, 11:56 p.m.
Created at: March 6, 2026, 9:47 p.m.