Triple

T19732739
Position Surface form Disambiguated ID Type / Status
Subject Maniema Province E473894 entity
Predicate hasCity P316 FINISHED
Object Kibombo
Kibombo is a town in the Maniema Province of the Democratic Republic of the Congo, serving as a local administrative and trading center.
 E1393286 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: Kibombo | Statement: [Maniema Province, hasCity, Kibombo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kibombo
Context triple: [Maniema Province, hasCity, Kibombo]
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Chibombo
    Chibombo is a town in Zambia that serves as an important local center within the country's Central Province.
  • C. Kasibu
    Kasibu is a rural municipality in the province of Nueva Vizcaya in the Philippines, known for its mountainous terrain and agricultural economy.
  • D. Kilembe
    Kilembe is a town in western Uganda that serves as a common starting point for treks to the Rwenzori Mountains, including ascents of Margherita Peak.
  • E. Butiama
    Butiama is a village in northern Tanzania best known as the birthplace and hometown of the country’s founding president, Julius Nyerere.
  • 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: Kibombo
Triple: [Maniema Province, hasCity, Kibombo]
Generated description
Kibombo is a town in the Maniema Province of the Democratic Republic of the Congo, serving as a local administrative and trading center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kibombo
Target entity description: Kibombo is a town in the Maniema Province of the Democratic Republic of the Congo, serving as a local administrative and trading center.
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Chibombo
    Chibombo is a town in Zambia that serves as an important local center within the country's Central Province.
  • C. Kasibu
    Kasibu is a rural municipality in the province of Nueva Vizcaya in the Philippines, known for its mountainous terrain and agricultural economy.
  • D. Kilembe
    Kilembe is a town in western Uganda that serves as a common starting point for treks to the Rwenzori Mountains, including ascents of Margherita Peak.
  • E. Butiama
    Butiama is a village in northern Tanzania best known as the birthplace and hometown of the country’s founding president, Julius Nyerere.
  • 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_69d8e517ebd48190979ee76723bcfadf completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e651596b98819090bcaf05c7b74555 completed April 20, 2026, 4:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07b4f4e1e081908fca0b6513bb3bbb completed May 16, 2026, 12:06 a.m.
NEDg Description generation batch_6a07b73cc5a48190af0ab9da30c859b4 completed May 16, 2026, 12:15 a.m.
NED2 Entity disambiguation (via description) batch_6a07b81193d081908dfb19272b4df41b completed May 16, 2026, 12:19 a.m.
Created at: April 10, 2026, 1:47 p.m.