Triple

T7429752
Position Surface form Disambiguated ID Type / Status
Subject Kunene Region E171458 entity
Predicate borders P224 FINISHED
Object Erongo Region E89872 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: Erongo Region | Statement: [Kunene Region, borders, Erongo Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erongo Region
Context triple: [Kunene Region, borders, Erongo Region]
  • A. Erongo Region chosen
    Erongo Region is an administrative region on Namibia’s central western coast, known for its Atlantic shoreline, desert landscapes, and the coastal town of Swakopmund.
  • B. Oshana Region
    Oshana Region is an administrative region in northern Namibia known for its flat, seasonally flooded plains and role as a key agricultural and population center.
  • C. Kunene Region
    Kunene Region is a sparsely populated, northwestern region of Namibia known for its rugged landscapes, desert-adapted wildlife, and remote Atlantic coastline.
  • D. Ohangwena Region
    Ohangwena Region is an administrative region in northern Namibia, known for its dense rural population and location along the border with Angola.
  • E. Omaheke Region
    Omaheke Region is an administrative region in eastern Namibia known for its semi-arid savannah landscapes and cattle farming.
  • 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_69c83c51901081908ad8513c860408eb completed March 28, 2026, 8:38 p.m.
Created at: March 27, 2026, 3:12 p.m.