Triple

T4149681
Position Surface form Disambiguated ID Type / Status
Subject Erongo Region E89872 entity
Predicate hasBorderWith P224 FINISHED
Object Kunene Region E171458 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: Kunene Region | Statement: [Erongo Region, hasBorderWith, Kunene Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kunene Region
Context triple: [Erongo Region, hasBorderWith, Kunene Region]
  • A. Kunene Region chosen
    Kunene Region is a sparsely populated, northwestern region of Namibia known for its rugged landscapes, desert-adapted wildlife, and remote Atlantic coastline.
  • B. Omaheke Region
    Omaheke Region is an administrative region in eastern Namibia known for its semi-arid savannah landscapes and cattle farming.
  • C. Ohangwena Region
    Ohangwena Region is an administrative region in northern Namibia, known for its dense rural population and location along the border with Angola.
  • D. Lindi Region
    Lindi Region is a coastal administrative region in southern Tanzania known for its historical Swahili settlements and Indian Ocean shoreline.
  • E. Otjozondjupa Region
    Otjozondjupa Region is an administrative region in central Namibia known for its agricultural activities, wildlife areas, and role as a key transport corridor.
  • 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_69aed95a59a881909b26e70b42c6811a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0273a038819087db092da234e767 completed March 9, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5960e8e3c8190b8eb9ed59971aa63 completed March 14, 2026, 5:08 p.m.
Created at: March 9, 2026, 3:43 p.m.