Triple

T21417871
Position Surface form Disambiguated ID Type / Status
Subject Wa E528353 entity
Predicate hasRoadConnectionTo P11435 FINISHED
Object Kumasi NE NERFINISHED

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: Kumasi | Statement: [Wa, hasRoadConnectionTo, Kumasi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kumasi
Context triple: [Wa, hasRoadConnectionTo, Kumasi]
  • A. Kumasi chosen
    Kumasi is a major city in southern Ghana, known as the historic capital of the Ashanti Kingdom and a key cultural and commercial center in West Africa.
  • B. Koforidua
    Koforidua is a major city in southern Ghana known as an administrative, commercial, and transportation hub for the Eastern Region.
  • C. Mampong
    Mampong is a prominent town and municipal center in Ghana known for its historical significance within the Ashanti cultural area and its role as an educational and agricultural hub.
  • D. Takoradi
    Takoradi is a coastal city in southwestern Ghana that developed into a key commercial and industrial hub, particularly known for its deep-water seaport and role in regional trade.
  • E. Kpando
    Kpando is a town in Ghana’s Volta Region, known as a local commercial center near the Volta Lake.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c454c248819093425d1099101c09 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee62d29f948190b820c92014d1c53a completed April 26, 2026, 7:09 p.m.
Created at: April 16, 2026, 5:46 p.m.