Triple

T1340555
Position Surface form Disambiguated ID Type / Status
Subject Bambara E28452 entity
Predicate closelyRelatedTo P37 FINISHED
Object Maninka E28118 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: Maninka | Statement: [Bambara, closelyRelatedTo, Maninka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maninka
Context triple: [Bambara, closelyRelatedTo, Maninka]
  • A. Lemi
    Lemi is a small rural municipality in southeastern Finland known for its lakes, forests, and traditional Karelian culture.
  • B. Nabaneeta
    Nabaneeta is a feminine given name most notably borne by the acclaimed Indian Bengali writer and academic Nabaneeta Dev Sen.
  • C. Mangina
    Mangina is a town in North Kivu Province in the eastern Democratic Republic of the Congo that gained international attention as a focal point of the 2018–2020 Kivu Ebola epidemic.
  • D. Maashees
    Maashees is a small village in the Dutch province of North Brabant, situated along the river Meuse and known for its rural character and historic church.
  • E. Mandinka chosen
    Mandinka is a major Mande language spoken primarily in The Gambia, Senegal, Guinea-Bissau, and neighboring West African countries by the Mandinka people.
  • 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_69a49854eb3481908c7d56b2e449a290 completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c21490488190b4281a16c87677d1 completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc6305c988190830dd535726c6338 completed March 8, 2026, 12:43 a.m.
Created at: March 1, 2026, 7:56 p.m.