Triple

T16983017
Position Surface form Disambiguated ID Type / Status
Subject Kwanza River E411991 entity
Predicate flowsThrough P225 FINISHED
Object Luanda Province E337756 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: Luanda Province | Statement: [Kwanza River, flowsThrough, Luanda Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luanda Province
Context triple: [Kwanza River, flowsThrough, Luanda Province]
  • A. Luanda Province chosen
    Luanda Province is a coastal region of Angola that includes the nation’s capital city, Luanda, and serves as a major political, economic, and cultural center.
  • B. Kinshasa Province
    Kinshasa Province is the administrative region encompassing the city of Kinshasa, the capital and largest urban center of the Democratic Republic of the Congo.
  • C. Moyen-Ogooué Province
    Moyen-Ogooué Province is an inland region of west-central Gabon known for its location along the Ogooué River and its capital, Lambaréné.
  • D. Haut-Ogooué Province
    Haut-Ogooué Province is a resource-rich administrative region in southeastern Gabon known for its mining industry and diverse ethnic communities.
  • E. Ogooué-Maritime Province
    Ogooué-Maritime Province is a coastal region in western Gabon known for its Atlantic shoreline, rich biodiversity, and inclusion of protected areas such as Loango National Park.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d188ede48190baead48aac84c78d completed April 18, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc0d437c81908f003a10b798998a completed May 10, 2026, 7:27 p.m.
Created at: April 10, 2026, 5:32 a.m.