Triple

T37048925
Position Surface form Disambiguated ID Type / Status
Subject Mwimbi dialect E916996 entity
Predicate spokenBy P2181 FINISHED
Object Mwimbi people
The Mwimbi people are an ethnic community in Kenya, traditionally inhabiting the eastern slopes of Mount Kenya and closely related to other Meru subgroups in language and culture.
E2297775 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: Mwimbi people | Statement: [Mwimbi dialect, spokenBy, Mwimbi 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: Mwimbi people
Triple: [Mwimbi dialect, spokenBy, Mwimbi people]
Generated description
The Mwimbi people are an ethnic community in Kenya, traditionally inhabiting the eastern slopes of Mount Kenya and closely related to other Meru subgroups in language and culture.

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_69f76e94d0308190a3f06890e133c88e completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fa016cb5248190a3f45fbe8b66a09c completed May 5, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a83d2016cc08190bf6be2a00f2dac01 completed Aug. 18, 2026, 3:31 a.m.
NEDg Description generation batch_6a83d258cabc819090e4d24a8ed6738d completed Aug. 18, 2026, 3:32 a.m.
NED2 Entity disambiguation (via description) batch_6a83d2b095988190b144a3f40dfb72a5 completed Aug. 18, 2026, 3:34 a.m.
Created at: May 3, 2026, 4:14 p.m.