Triple

T841528
Position Surface form Disambiguated ID Type / Status
Subject Southern Africa E18188 entity
Predicate hasCountry P846 FINISHED
Object Eswatini E16080 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: Eswatini | Statement: [Southern Africa, hasCountry, Eswatini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eswatini
Context triple: [Southern Africa, hasCountry, Eswatini]
  • A. Eswatini chosen
    Eswatini is a small landlocked monarchy in Southern Africa known for its blend of traditional Swazi culture and modern institutions.
  • B. Lesotho
    Lesotho is a small, landlocked constitutional monarchy in Southern Africa, entirely surrounded by South Africa and known for its mountainous terrain and high-altitude settlements.
  • C. Botswana
    Botswana is a landlocked country in Southern Africa known for its stable democracy, significant diamond resources, and vast wildlife-rich landscapes including the Okavango Delta.
  • D. Zimbabwe
    Zimbabwe is a landlocked country in southern Africa known for its dramatic landscapes, diverse wildlife, and historical sites such as Victoria Falls and the Great Zimbabwe ruins.
  • E. Botswana and Zimbabwe
    Botswana and Zimbabwe are neighboring landlocked countries in Southern Africa that share close historical, economic, and ecological ties.
  • 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_69a49389f44881909a608fb27d89f247 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4abe6f0dc8190a1bebb5e21f4ceac completed March 1, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae1f9fcac481909cb3f6c6dc681e60 completed March 9, 2026, 1:17 a.m.
Created at: March 1, 2026, 7:38 p.m.