Triple

T1827956
Position Surface form Disambiguated ID Type / Status
Subject Kampala E40695 entity
Predicate locatedIn P40 FINISHED
Object Buganda
Buganda is a traditional Bantu kingdom in central Uganda that is the country’s most populous and historically influential region.
 E203300 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: Buganda | Statement: [Kampala, locatedIn, Buganda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Buganda
Context triple: [Kampala, locatedIn, Buganda]
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Igunga
    Igunga is a town and district in central Tanzania known for its agricultural activities, particularly cotton and livestock farming, within the Tabora Region.
  • C. Mbanika
    Mbanika is one of the main islands in the Russell Islands group in the Central Province of the Solomon Islands, known for its World War II history and natural tropical environment.
  • D. Nzega
    Nzega is a town and district in western Tanzania that serves as an important commercial and transport hub within the Tabora Region.
  • E. Karanga
    Karanga is a major dialect of the Shona language spoken primarily in southern Zimbabwe, known for its distinct phonological and lexical features.
  • 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: Buganda
Triple: [Kampala, locatedIn, Buganda]
Generated description
Buganda is a traditional Bantu kingdom in central Uganda that is the country’s most populous and historically influential region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Buganda
Target entity description: Buganda is a traditional Bantu kingdom in central Uganda that is the country’s most populous and historically influential region.
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Igunga
    Igunga is a town and district in central Tanzania known for its agricultural activities, particularly cotton and livestock farming, within the Tabora Region.
  • C. Mbanika
    Mbanika is one of the main islands in the Russell Islands group in the Central Province of the Solomon Islands, known for its World War II history and natural tropical environment.
  • D. Nzega
    Nzega is a town and district in western Tanzania that serves as an important commercial and transport hub within the Tabora Region.
  • E. Karanga
    Karanga is a major dialect of the Shona language spoken primarily in southern Zimbabwe, known for its distinct phonological and lexical features.
  • 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_69a8864644bc8190b2358ab897194ac1 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb01191208190a7eaf3036638ec40 completed March 7, 2026, 4:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf6b4bdc8190b53dbdc9c31e3685 completed March 8, 2026, 6:26 p.m.
NEDg Description generation batch_69adc07fff60819092b10dd0e417ac5a completed March 8, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69adc0fd79c48190864f53a90517edc6 completed March 8, 2026, 6:33 p.m.
Created at: March 4, 2026, 7:32 p.m.