Triple

T13804641
Position Surface form Disambiguated ID Type / Status
Subject Eastern Region of Uganda E331727 entity
Predicate hasUrbanCenter P2106 FINISHED
Object Soroti E329617 NE FINISHED

How this triple was built (2 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: Soroti | Statement: [Eastern Region of Uganda, hasUrbanCenter, Soroti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Soroti
Context triple: [Eastern Region of Uganda, hasUrbanCenter, Soroti]
  • A. Soroti chosen
    Soroti is a town in eastern Uganda that serves as a regional commercial and administrative center.
  • B. Mbarara
    Mbarara is a major city in southwestern Uganda that serves as a key commercial and transport hub for the region.
  • C. Soroti District
    Soroti District is an administrative district in eastern Uganda known for its agricultural economy and as the area surrounding the town of Soroti.
  • D. Kasese
    Kasese is a town in western Uganda that serves as a key gateway to Queen Elizabeth National Park and the Rwenzori Mountains.
  • E. Nimule
    Nimule is a South Sudanese border town near Uganda that serves as a key trade and transport hub in the region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de026c36108190a7436034a730a261 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0e5251c81909f3f40dcdea1772f completed May 3, 2026, 9:40 p.m.
Created at: April 9, 2026, 10:12 p.m.