Triple

T4837680
Position Surface form Disambiguated ID Type / Status
Subject Dar es Salaam E108100 entity
Predicate hasDistrict P459 FINISHED
Object Kinondoni
Kinondoni is a major urban district within Dar es Salaam, Tanzania, known for its dense population, commercial activity, and diverse residential neighborhoods.
 E480186 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: Kinondoni | Statement: [Dar es Salaam, hasDistrict, Kinondoni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kinondoni
Context triple: [Dar es Salaam, hasDistrict, Kinondoni]
  • A. Masindi
    Masindi is a town in western Uganda that serves as a key gateway and service center for visitors to Murchison Falls National Park.
  • B. Nairobi
    Nairobi is the capital and largest city of Kenya, serving as a major political, economic, and cultural hub in East Africa.
  • C. Nairobi
    Nairobi is a fan-favorite character from the Spanish series "Money Heist," known for her sharp leadership, optimism, and expertise in overseeing the gang’s money-printing operations.
  • D. Dar es Salaam
    Dar es Salaam is a major coastal metropolis on the Indian Ocean and the principal economic and commercial hub of Tanzania.
  • E. Manzini
    Manzini is a major city in Eswatini that serves as an important commercial and transport hub of the country.
  • 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: Kinondoni
Triple: [Dar es Salaam, hasDistrict, Kinondoni]
Generated description
Kinondoni is a major urban district within Dar es Salaam, Tanzania, known for its dense population, commercial activity, and diverse residential neighborhoods.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kinondoni
Target entity description: Kinondoni is a major urban district within Dar es Salaam, Tanzania, known for its dense population, commercial activity, and diverse residential neighborhoods.
  • A. Masindi
    Masindi is a town in western Uganda that serves as a key gateway and service center for visitors to Murchison Falls National Park.
  • B. Nairobi
    Nairobi is the capital and largest city of Kenya, serving as a major political, economic, and cultural hub in East Africa.
  • C. Nairobi
    Nairobi is a fan-favorite character from the Spanish series "Money Heist," known for her sharp leadership, optimism, and expertise in overseeing the gang’s money-printing operations.
  • D. Dar es Salaam
    Dar es Salaam is a major coastal metropolis on the Indian Ocean and the principal economic and commercial hub of Tanzania.
  • E. Manzini
    Manzini is a major city in Eswatini that serves as an important commercial and transport hub of the country.
  • 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_69be778cace48190ad28eaf21aec7146 completed March 21, 2026, 10:48 a.m.
NEDg Description generation batch_69be783708d48190ad8d48e16e771b19 completed March 21, 2026, 10:51 a.m.
NED2 Entity disambiguation (via description) batch_69be78a0bdc88190bd8458658f15f879 completed March 21, 2026, 10:53 a.m.
Created at: March 20, 2026, 1:25 p.m.