Triple

T7429745
Position Surface form Disambiguated ID Type / Status
Subject Kunene Region E171458 entity
Predicate country P26 FINISHED
Object Namibia E14828 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: Namibia | Statement: [Kunene Region, country, Namibia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namibia
Context triple: [Kunene Region, country, Namibia]
  • A. Namibia chosen
    Namibia is a sparsely populated country in southwestern Africa known for its dramatic desert landscapes, diverse wildlife, and a legal system influenced by Roman-Dutch law.
  • B. 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.
  • C. Namibia and Botswana
    Namibia and Botswana are neighboring countries in Southern Africa known for their vast deserts, rich wildlife, and major river systems that shape their shared ecosystems and borders.
  • D. Eswatini
    Eswatini is a small landlocked monarchy in Southern Africa known for its blend of traditional Swazi culture and modern institutions.
  • E. 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.
  • 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_69c68a63491881909281f73d4d5643bf completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f3082f188190af5673d18ac7e87e completed March 27, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83449b84c81909167f29e901c0881 completed March 28, 2026, 8:04 p.m.
Created at: March 27, 2026, 3:12 p.m.