Triple

T1530130
Position Surface form Disambiguated ID Type / Status
Subject Zambezi Valley E32420 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: [Zambezi Valley, country, Namibia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namibia
Context triple: [Zambezi Valley, 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908156b888190968ca0157ae42bc7 completed March 5, 2026, 4:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7ed1080081909a931e4d045edd83 completed March 9, 2026, 8:03 a.m.
Created at: March 4, 2026, 7:26 p.m.