Triple

T11921613
Position Surface form Disambiguated ID Type / Status
Subject Kiryandongo District E283669 entity
Predicate capital P234 FINISHED
Object Kiryandongo
Kiryandongo is a town in western Uganda that serves as the administrative and commercial center of Kiryandongo District.
E957690 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: Kiryandongo | Statement: [Kiryandongo District, capital, Kiryandongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiryandongo
Context triple: [Kiryandongo District, capital, Kiryandongo]
  • A. Bunyoro
    Bunyoro is a traditional kingdom and historical region in western Uganda that was once a powerful pre-colonial African state.
  • B. Nimule
    Nimule is a South Sudanese border town near Uganda that serves as a key trade and transport hub in the region.
  • C. Gokwe
    Gokwe is a town in central Zimbabwe known for its cotton farming and role as a commercial hub in the Midlands Province.
  • D. Owendo
    Owendo is a port city in western Gabon that serves as an important industrial and maritime hub near the capital, Libreville.
  • E. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma 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: Kiryandongo
Triple: [Kiryandongo District, capital, Kiryandongo]
Generated description
Kiryandongo is a town in western Uganda that serves as the administrative and commercial center of Kiryandongo District.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kiryandongo
Target entity description: Kiryandongo is a town in western Uganda that serves as the administrative and commercial center of Kiryandongo District.
  • A. Bunyoro
    Bunyoro is a traditional kingdom and historical region in western Uganda that was once a powerful pre-colonial African state.
  • B. Nimule
    Nimule is a South Sudanese border town near Uganda that serves as a key trade and transport hub in the region.
  • C. Gokwe
    Gokwe is a town in central Zimbabwe known for its cotton farming and role as a commercial hub in the Midlands Province.
  • D. Owendo
    Owendo is a port city in western Gabon that serves as an important industrial and maritime hub near the capital, Libreville.
  • E. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma 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_69d6ab2ce9c48190b5d39511b524f666 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e8e1b08481909ed291667035f330 completed April 10, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f47195df0c8190a27abfe58f221f59 completed May 1, 2026, 9:25 a.m.
NEDg Description generation batch_69f47b755f808190acb2fb31473d2405 completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47d8bbae8819088d48b300291ef74 completed May 1, 2026, 10:16 a.m.
Created at: April 8, 2026, 9:45 p.m.