Triple

T23437658
Position Surface form Disambiguated ID Type / Status
Subject Kumasi Fort E563508 entity
Predicate locatedIn P40 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: [Kumasi Fort, locatedIn, Kumasi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kumasi
Context triple: [Kumasi Fort, locatedIn, 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_69e24553980c8190bb66a2ae0bdab125 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a5dda7448190b6c686e0db4f4f2f completed April 29, 2026, 6:31 a.m.
Created at: April 17, 2026, 5:50 p.m.