Triple

T3041621
Position Surface form Disambiguated ID Type / Status
Subject Commonwealth of Nations E83142 entity
Predicate hasMemberState P5029 FINISHED
Object Uganda E10768 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: Uganda | Statement: [Commonwealth of Nations, hasMemberState, Uganda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uganda
Context triple: [Commonwealth of Nations, hasMemberState, Uganda]
  • A. Uganda chosen
    Uganda is a landlocked country in East Africa known for its diverse landscapes, abundant wildlife, and location along the equator.
  • B. Oluganda
    Oluganda is the endonym for Luganda, a major Bantu language spoken primarily by the Baganda people in central Uganda.
  • C. Nzera
    Nzera is a settlement located within Tanzania’s Geita Region in East Africa.
  • D. Kenya
    Kenya is an East African country known for its diverse wildlife, scenic landscapes from savannas to highlands, and a coastline along the Indian Ocean.
  • E. Democratic Republic of the Congo
    The Democratic Republic of the Congo is a vast, resource-rich Central African nation known for the Congo River basin, extensive rainforests, and a history marked by colonial exploitation and ongoing political instability.
  • 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_69ad8b2298908190a7cb4e9bdbf064d0 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9b5b92088190971bed04e65c5917 completed March 8, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ded01a1481908be7d44c2bf4e638 completed March 11, 2026, 9:29 p.m.
Created at: March 8, 2026, 3:01 p.m.