Triple

T730957
Position Surface form Disambiguated ID Type / Status
Subject Namibia E14828 entity
Predicate capital P234 FINISHED
Object Windhoek E48226 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: Windhoek | Statement: [Namibia, capital, Windhoek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Windhoek
Context triple: [Namibia, capital, Windhoek]
  • A. Windhoek chosen
    Windhoek is the capital and largest city of Namibia, serving as the country’s political, economic, and cultural center.
  • B. Malabo
    Malabo is the largest city and main economic and administrative center of Equatorial Guinea, located on the northern coast of Bioko Island in the Gulf of Guinea.
  • C. Luanda
    Luanda is the capital and largest city of Angola, a major Atlantic port and economic hub with a history shaped by Portuguese colonial rule and the transatlantic slave trade.
  • D. Maseru
    Maseru is the largest city and administrative, economic, and cultural center of the Kingdom of Lesotho in southern Africa.
  • E. Lüderitz
    Lüderitz is a coastal town in southwestern Namibia known for its Atlantic shoreline, nearby desert landscapes, and rich marine ecosystem influenced by the Benguela Current.
  • 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5c40b6481909db9efd7310850b3 completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6666ebf2c8190b0b0f1b9aa8ac12d completed March 3, 2026, 4:41 a.m.
Created at: March 1, 2026, 7:37 p.m.