Triple

T14788788
Position Surface form Disambiguated ID Type / Status
Subject Denkyira E347597 entity
Predicate hadVassal P7255 FINISHED
Object Kumasi E156961 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: Kumasi | Statement: [Denkyira, hadVassal, Kumasi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kumasi
Context triple: [Denkyira, hadVassal, 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. Obuasi
    Obuasi is a major Ghanaian mining town renowned for its large gold deposits and historic gold mine.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decaa1e9ec81908d7c26c1c4e43014 completed April 14, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe72a4f71881909c3c1cc09fe89a60 completed May 8, 2026, 11:32 p.m.
Created at: April 10, 2026, 1:31 a.m.