Triple

T7492656
Position Surface form Disambiguated ID Type / Status
Subject Shinyanga Region E177042 entity
Predicate administrativeCenter P1474 FINISHED
Object Shinyanga
Shinyanga is a town in northern Tanzania that serves as a commercial hub and key transport center for the surrounding region.
 E177042 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: Shinyanga | Statement: [Shinyanga Region, administrativeCenter, Shinyanga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shinyanga
Context triple: [Shinyanga Region, administrativeCenter, Shinyanga]
  • A. Shinyanga Region
    Shinyanga Region is an administrative region in northwestern Tanzania known for its agriculture, mining activities, and proximity to Lake Victoria.
  • B. Nyamwezi
    Nyamwezi is a Bantu language spoken primarily in northwestern Tanzania by the Nyamwezi people.
  • C. Nyanga
    Nyanga is a township on the Cape Flats near Cape Town, South Africa, known for its history of apartheid-era resistance and ongoing social and economic challenges.
  • D. Soroti
    Soroti is a town in eastern Uganda that serves as a regional commercial and administrative center.
  • E. Kasese
    Kasese is a town in western Uganda that serves as a key gateway to Queen Elizabeth National Park and the Rwenzori Mountains.
  • 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: Shinyanga
Triple: [Shinyanga Region, administrativeCenter, Shinyanga]
Generated description
Shinyanga is a town in northern Tanzania that serves as a commercial hub and key transport center for the surrounding region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shinyanga
Target entity description: Shinyanga is a town in northern Tanzania that serves as a commercial hub and key transport center for the surrounding region.
  • A. Shinyanga Region chosen
    Shinyanga Region is an administrative region in northwestern Tanzania known for its agriculture, mining activities, and proximity to Lake Victoria.
  • B. Nyamwezi
    Nyamwezi is a Bantu language spoken primarily in northwestern Tanzania by the Nyamwezi people.
  • C. Nyanga
    Nyanga is a township on the Cape Flats near Cape Town, South Africa, known for its history of apartheid-era resistance and ongoing social and economic challenges.
  • D. Soroti
    Soroti is a town in eastern Uganda that serves as a regional commercial and administrative center.
  • E. Kasese
    Kasese is a town in western Uganda that serves as a key gateway to Queen Elizabeth National Park and the Rwenzori Mountains.
  • 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_69c69f2583808190bd1a4936c42a5815 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5784c908190b701959daf082625 completed March 27, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84600d65481908518bc0d7ffcb373 completed March 28, 2026, 9:20 p.m.
NEDg Description generation batch_69c8464ec5ec8190be718a1508e8e53b completed March 28, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_69c846b86a888190bc09bc17a5df252b completed March 28, 2026, 9:23 p.m.
Created at: March 27, 2026, 3:43 p.m.