Triple

T17973833
Position Surface form Disambiguated ID Type / Status
Subject Dagomba people E449412 entity
Predicate historicalLanguageRelation P7165 FINISHED
Object Nanumba people
The Nanumba people are an ethnic group in northern Ghana closely related culturally and linguistically to neighboring Dagomba and other Mole-Dagbani groups.
E1735886 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: Nanumba people | Statement: [Dagomba people, historicalLanguageRelation, Nanumba people]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nanumba people
Triple: [Dagomba people, historicalLanguageRelation, Nanumba people]
Generated description
The Nanumba people are an ethnic group in northern Ghana closely related culturally and linguistically to neighboring Dagomba and other Mole-Dagbani groups.

Provenance (5 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_69d8b9f9927c8190a006110c8b996e61 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b1fe24808190baa11739f4d1095f completed April 19, 2026, 10:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a11ebe189408190a1aa02b093912dcb completed May 23, 2026, 6:03 p.m.
NEDg Description generation batch_6a11ef2bf6fc81908c9073c3deca6ebf completed May 23, 2026, 6:17 p.m.
NED2 Entity disambiguation (via description) batch_6a11ef8994048190aca5d61de927d20c completed May 23, 2026, 6:18 p.m.
Created at: April 10, 2026, 10:22 a.m.