Triple

T6580054
Position Surface form Disambiguated ID Type / Status
Subject Kisangani E157267 entity
Predicate partOf P40 FINISHED
Object Congo Basin E55301 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: Congo Basin | Statement: [Kisangani, partOf, Congo Basin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Congo Basin
Context triple: [Kisangani, partOf, Congo Basin]
  • A. Congo Rainforest chosen
    The Congo Rainforest is the world’s second-largest tropical rainforest, a vast biodiversity hotspot in Central Africa that plays a crucial role in global climate regulation and carbon storage.
  • B. Banda Basin
    The Banda Basin is a deep oceanic basin in eastern Indonesia, known for its complex tectonic setting and very deep waters within the Banda Sea region.
  • C. Kongo Jungle
    Kongo Jungle is a lush, tropical jungle region in the Donkey Kong video game series, often serving as the iconic home and starting area for Donkey Kong and his friends.
  • D. Congo
    Congo is a Central African country whose economy is heavily reliant on oil production and exports.
  • E. Bandama River basin
    The Bandama River basin is the largest river drainage system in Côte d'Ivoire, encompassing much of the country's central region and supporting agriculture, settlements, and hydropower.
  • 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_69c6882b3a108190b3a9eb343ae4162c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae8ef4d08190b4c88aa0c15fe91c completed March 27, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d572c4708190844f4b1abee8ca86 completed March 27, 2026, 7:07 p.m.
Created at: March 27, 2026, 1:54 p.m.