Triple

T1806239
Position Surface form Disambiguated ID Type / Status
Subject Nairobi River E40225 entity
Predicate flowsThrough P225 FINISHED
Object Mathare
Mathare is a densely populated informal settlement and neighborhood in Nairobi, Kenya, known for its extensive slums and socio-economic challenges.
 E216465 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: Mathare | Statement: [Nairobi River, flowsThrough, Mathare]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mathare
Context triple: [Nairobi River, flowsThrough, Mathare]
  • A. Kibera
    Kibera is one of Africa’s largest informal settlements, located in Nairobi, Kenya, known for its dense population, poverty, and vibrant community life.
  • B. Mbare
    Mbare is one of the oldest and most densely populated townships in Harare, Zimbabwe, known as a major transport hub and bustling market area.
  • C. Kadoma
    Kadoma is a city in Osaka Prefecture, Japan, known as a residential and commercial suburb within the Osaka metropolitan area.
  • D. Embakasi
    Embakasi is a residential and industrial area in Nairobi, Kenya, known for hosting key infrastructure and serving as a major gateway corridor to the city.
  • E. Nairobi
    Nairobi is the capital and largest city of Kenya, serving as a major political, economic, and cultural hub in East Africa.
  • 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: Mathare
Triple: [Nairobi River, flowsThrough, Mathare]
Generated description
Mathare is a densely populated informal settlement and neighborhood in Nairobi, Kenya, known for its extensive slums and socio-economic challenges.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mathare
Target entity description: Mathare is a densely populated informal settlement and neighborhood in Nairobi, Kenya, known for its extensive slums and socio-economic challenges.
  • A. Kibera
    Kibera is one of Africa’s largest informal settlements, located in Nairobi, Kenya, known for its dense population, poverty, and vibrant community life.
  • B. Mbare
    Mbare is one of the oldest and most densely populated townships in Harare, Zimbabwe, known as a major transport hub and bustling market area.
  • C. Kadoma
    Kadoma is a city in Osaka Prefecture, Japan, known as a residential and commercial suburb within the Osaka metropolitan area.
  • D. Embakasi
    Embakasi is a residential and industrial area in Nairobi, Kenya, known for hosting key infrastructure and serving as a major gateway corridor to the city.
  • E. Nairobi
    Nairobi is the capital and largest city of Kenya, serving as a major political, economic, and cultural hub in East Africa.
  • 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_69a88643a3388190a612f2ebe1fb29e7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa659798b88190bd3070349ce6bebb completed March 6, 2026, 5:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3c192f08190a1a134e541be1103 completed March 8, 2026, 10:10 p.m.
NEDg Description generation batch_69adf5b31274819086c266c1a8ba2cd8 completed March 8, 2026, 10:18 p.m.
NED2 Entity disambiguation (via description) batch_69adf6108c988190b992de20cf287da7 completed March 8, 2026, 10:20 p.m.
Created at: March 4, 2026, 7:32 p.m.