Triple

T16381865
Position Surface form Disambiguated ID Type / Status
Subject Ohangwena Region E397824 entity
Predicate hasSettlement P1068 FINISHED
Object Oshikango E893228 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: Oshikango | Statement: [Ohangwena Region, hasSettlement, Oshikango]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oshikango
Context triple: [Ohangwena Region, hasSettlement, Oshikango]
  • A. Oshikango chosen
    Oshikango is a border town in northern Namibia that serves as a key commercial and transport hub between Namibia and Angola.
  • B. Shiroro
    Shiroro is a town in Niger State, Nigeria, known for hosting the major hydroelectric Shiroro Dam on the Kaduna River.
  • C. Rutshuru
    Rutshuru is a town in the eastern Democratic Republic of the Congo known for its strategic location near the borders with Rwanda and Uganda and its history of conflict and humanitarian challenges.
  • D. Ishkashimi
    Ishkashimi is a lesser-known Eastern Iranian language spoken by small communities in parts of Afghanistan and Tajikistan.
  • E. Mitoyo
    Mitoyo is a coastal city in western Kagawa Prefecture on Japan’s Shikoku Island, known for its scenic Seto Inland Sea views and rural landscapes.
  • 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e319dd0e0c8190812bde6a2f7d9644 completed April 18, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f41703c81908fb040a9107045ae completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:08 a.m.