Triple

T249649
Position Surface form Disambiguated ID Type / Status
Subject Kigoma Region E5115 entity
Predicate largestCity P235 FINISHED
Object Kigoma
Kigoma is a major town in western Tanzania located on the eastern shore of Lake Tanganyika and serving as an important regional transport and trade hub.
 E5115 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: Kigoma | Statement: [Kigoma Region, largestCity, Kigoma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kigoma
Context triple: [Kigoma Region, largestCity, Kigoma]
  • A. Kigoma Region
    Kigoma Region is a western Tanzanian administrative region along Lake Tanganyika, known for its biodiversity and as a center for primate research.
  • B. Mutare
    Mutare is a major city in eastern Zimbabwe, serving as the capital of Manicaland Province and an important commercial and transport hub near the border with Mozambique.
  • C. Masvingo
    Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
  • D. Kiunguja
    Kiunguja is the Zanzibar-based variety of Swahili that historically served as the primary basis for the standardized form of the language.
  • E. Tanzania
    Tanzania is an East African nation known for its vast wilderness areas, including the Serengeti National Park and Mount Kilimanjaro, as well as its rich cultural diversity.
  • 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: Kigoma
Triple: [Kigoma Region, largestCity, Kigoma]
Generated description
Kigoma is a major town in western Tanzania located on the eastern shore of Lake Tanganyika and serving as an important regional transport and trade hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kigoma
Target entity description: Kigoma is a major town in western Tanzania located on the eastern shore of Lake Tanganyika and serving as an important regional transport and trade hub.
  • A. Kigoma Region chosen
    Kigoma Region is a western Tanzanian administrative region along Lake Tanganyika, known for its biodiversity and as a center for primate research.
  • B. Mutare
    Mutare is a major city in eastern Zimbabwe, serving as the capital of Manicaland Province and an important commercial and transport hub near the border with Mozambique.
  • C. Masvingo
    Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
  • D. Kiunguja
    Kiunguja is the Zanzibar-based variety of Swahili that historically served as the primary basis for the standardized form of the language.
  • E. Tanzania
    Tanzania is an East African nation known for its vast wilderness areas, including the Serengeti National Park and Mount Kilimanjaro, as well as its rich cultural diversity.
  • 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_69a257c4bf688190a46ebbf411ab7473 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25d3728f0819086214ccc2db2305a completed Feb. 28, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3765be530819088d680acc6a26a4a completed Feb. 28, 2026, 11:12 p.m.
NEDg Description generation batch_69a376cfa62c8190967fd7477e8440ab completed Feb. 28, 2026, 11:14 p.m.
NED2 Entity disambiguation (via description) batch_69a3772b8a848190b5367ba2e64c6a43 completed Feb. 28, 2026, 11:15 p.m.
Created at: Feb. 28, 2026, 2:54 a.m.