Triple

T648456
Position Surface form Disambiguated ID Type / Status
Subject Kenya E11292 entity
Predicate borderCountry P224 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: [Kenya, borderCountry, Uganda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uganda
Context triple: [Kenya, borderCountry, 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. 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.
  • C. 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.
  • D. Rwanda
    Rwanda is a landlocked East African nation known for its dramatic recovery from the 1994 genocide, rapid economic growth, and strong conservation efforts, particularly for mountain gorillas.
  • E. Zambia
    Zambia is a landlocked country in south-central Africa known for the Victoria Falls on the Zambezi River, diverse wildlife, and copper-rich economy.
  • 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f308f34819094ba28cfc786051e completed March 1, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7edf404008190bde0280a67c12b5a completed March 4, 2026, 8:31 a.m.
Created at: March 1, 2026, 7:36 p.m.