Triple

T16893913
Position Surface form Disambiguated ID Type / Status
Subject Erongo Mountains E424247 entity
Predicate near P350 FINISHED
Object Omaruru E417648 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: Omaruru | Statement: [Erongo Mountains, near, Omaruru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Omaruru
Context triple: [Erongo Mountains, near, Omaruru]
  • A. Omaruru chosen
    Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming center.
  • B. Tsumkwe
    Tsumkwe is a remote settlement in northeastern Namibia known as a center of San (Bushmen) communities and culture.
  • C. Gwembe
    Gwembe is a small town in southern Zambia situated near the Zambezi Valley, historically associated with Tonga communities and resettlement related to the Kariba Dam.
  • D. Lobatse
    Lobatse is a town in southeastern Botswana known as an early administrative and industrial center, located south of Gaborone near the South African border.
  • E. Bongwe
    Bongwe is a dialect of the Duala language spoken by the Duala people of Cameroon.
  • 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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3c8d6bfc88190b6b47b89c1135871 completed April 18, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7aa83bc8190832d2f3903ce0081 completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:29 a.m.