Triple

T11773204
Position Surface form Disambiguated ID Type / Status
Subject Kisolongo E279950 entity
Predicate hasAlternativeName P39 FINISHED
Object Kisongo
Kisongo is a locality whose name is used as an alternative designation for the place known as Kisolongo.
E279950 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: Kisongo | Statement: [Kisolongo, hasAlternativeName, Kisongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kisongo
Context triple: [Kisolongo, hasAlternativeName, Kisongo]
  • A. Kisolongo
    Kisolongo is a regional dialect of the Kikongo language spoken by Kongo communities in parts of Central Africa.
  • B. Mikongo
    Mikongo is a small settlement in central Gabon that serves as a key access point for visitors exploring Lope National Park.
  • C. Kisoro
    Kisoro is a small town in southwestern Uganda known as a gateway to gorilla trekking and the nearby Bwindi Impenetrable and Mgahinga Gorilla National Parks.
  • D. Kasangati
    Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
  • 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: Kisongo
Triple: [Kisolongo, hasAlternativeName, Kisongo]
Generated description
Kisongo is a locality whose name is used as an alternative designation for the place known as Kisolongo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kisongo
Target entity description: Kisongo is a locality whose name is used as an alternative designation for the place known as Kisolongo.
  • A. Kisolongo chosen
    Kisolongo is a regional dialect of the Kikongo language spoken by Kongo communities in parts of Central Africa.
  • B. Mikongo
    Mikongo is a small settlement in central Gabon that serves as a key access point for visitors exploring Lope National Park.
  • C. Kisoro
    Kisoro is a small town in southwestern Uganda known as a gateway to gorilla trekking and the nearby Bwindi Impenetrable and Mgahinga Gorilla National Parks.
  • D. Kasangati
    Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
  • 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.

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_69d6ab01d2688190ad8ed6bda487eaa5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a55dfa088190a59b35d0247225e3 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f130cb31f48190a9357cce47a7b192 completed April 28, 2026, 10:12 p.m.
NEDg Description generation batch_69f14e879aa88190a95f13e23dd346f4 completed April 29, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_69f156fa5cc48190a43c1d2e5df346fe completed April 29, 2026, 12:55 a.m.
Created at: April 8, 2026, 9:41 p.m.