Triple

T4837683
Position Surface form Disambiguated ID Type / Status
Subject Dar es Salaam E108100 entity
Predicate hasDistrict P459 FINISHED
Object Kigamboni
Kigamboni is a coastal district of Dar es Salaam in Tanzania, known for its beaches, port facilities, and rapidly growing urban and residential developments.
 E475401 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: Kigamboni | Statement: [Dar es Salaam, hasDistrict, Kigamboni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kigamboni
Context triple: [Dar es Salaam, hasDistrict, Kigamboni]
  • A. 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.
  • B. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • C. Chitambo
    Chitambo is a historical locality in present-day Zambia best known as the place where Scottish explorer David Livingstone died in 1873.
  • D. Butiama
    Butiama is a village in northern Tanzania best known as the birthplace and hometown of the country’s founding president, Julius Nyerere.
  • E. Mbagala
    "Mbagala" is a popular hit song by Tanzanian Bongo Flava artist Diamond Platnumz that helped establish his early fame 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: Kigamboni
Triple: [Dar es Salaam, hasDistrict, Kigamboni]
Generated description
Kigamboni is a coastal district of Dar es Salaam in Tanzania, known for its beaches, port facilities, and rapidly growing urban and residential developments.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kigamboni
Target entity description: Kigamboni is a coastal district of Dar es Salaam in Tanzania, known for its beaches, port facilities, and rapidly growing urban and residential developments.
  • A. 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.
  • B. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • C. Chitambo
    Chitambo is a historical locality in present-day Zambia best known as the place where Scottish explorer David Livingstone died in 1873.
  • D. Butiama
    Butiama is a village in northern Tanzania best known as the birthplace and hometown of the country’s founding president, Julius Nyerere.
  • E. Mbagala
    "Mbagala" is a popular hit song by Tanzanian Bongo Flava artist Diamond Platnumz that helped establish his early fame 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_69bd43fbe444819085cb970706ef73f7 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6ce2e810819089f9a3f2a7574d44 completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5cc054ac819099d6d3dbf415e710 completed March 21, 2026, 8:54 a.m.
NEDg Description generation batch_69be60d4fa0c8190b6d197eb3dbafff7 completed March 21, 2026, 9:11 a.m.
NED2 Entity disambiguation (via description) batch_69be61789d388190bc23d7f44cee2e5d completed March 21, 2026, 9:14 a.m.
Created at: March 20, 2026, 1:25 p.m.