Triple

T7994197
Position Surface form Disambiguated ID Type / Status
Subject Singida Region E186081 entity
Predicate hasSettlement P1068 FINISHED
Object Manyoni
Manyoni is a town and district headquarters in central Tanzania known for its location along major road and rail routes in the Singida Region.
 E711003 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: Manyoni | Statement: [Singida Region, hasSettlement, Manyoni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Manyoni
Context triple: [Singida Region, hasSettlement, Manyoni]
  • A. Nyanda
    Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
  • B. Mungaka
    Mungaka is a Grassfields Bantu language spoken primarily in Cameroon, particularly associated with the Bamunka (Ndop) area.
  • C. Mikongo
    Mikongo is a small settlement in central Gabon that serves as a key access point for visitors exploring Lope National Park.
  • D. Mwali
    Mwali is the local name for Mohéli, the smallest of the three main islands in the Union of the Comoros in the Indian Ocean.
  • E. Murambi
    Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
  • 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: Manyoni
Triple: [Singida Region, hasSettlement, Manyoni]
Generated description
Manyoni is a town and district headquarters in central Tanzania known for its location along major road and rail routes in the Singida Region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Manyoni
Target entity description: Manyoni is a town and district headquarters in central Tanzania known for its location along major road and rail routes in the Singida Region.
  • A. Nyanda
    Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
  • B. Mungaka
    Mungaka is a Grassfields Bantu language spoken primarily in Cameroon, particularly associated with the Bamunka (Ndop) area.
  • C. Mikongo
    Mikongo is a small settlement in central Gabon that serves as a key access point for visitors exploring Lope National Park.
  • D. Mwali
    Mwali is the local name for Mohéli, the smallest of the three main islands in the Union of the Comoros in the Indian Ocean.
  • E. Murambi
    Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
  • 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_69ca829c6c308190ab05b43d234c52b2 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c73ba388190bcedc29fbdd22f3c completed March 31, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63bcae048190a3fd151b2d8f9f77 completed April 1, 2026, 12:15 a.m.
NEDg Description generation batch_69cc64bd6a088190b77e2709c76579e4 completed April 1, 2026, 12:20 a.m.
NED2 Entity disambiguation (via description) batch_69cc66b0e1548190840e4335ff2b130f completed April 1, 2026, 12:28 a.m.
Created at: March 30, 2026, 5:16 p.m.