Triple

T24468121
Position Surface form Disambiguated ID Type / Status
Subject Kamba E617028 entity
Predicate spokenBy P2181 FINISHED
Object Akamba people
The Akamba people are a Bantu ethnic group primarily inhabiting eastern Kenya, known for their rich oral traditions, woodcarving, and long history as traders and farmers.
E2203667 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: Akamba people | Statement: [Kamba, spokenBy, Akamba 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: Akamba people
Triple: [Kamba, spokenBy, Akamba people]
Generated description
The Akamba people are a Bantu ethnic group primarily inhabiting eastern Kenya, known for their rich oral traditions, woodcarving, and long history as traders and farmers.

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_69e2d7f197588190889a03e620558059 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f299413ea88190b15e482035ff5a83 completed April 29, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfab53f1c8190a688a38394155a5f completed June 26, 2026, 4:06 a.m.
NEDg Description generation batch_6a3dfd07722c8190bce1f21b79d1edb9 completed June 26, 2026, 4:16 a.m.
NED2 Entity disambiguation (via description) batch_6a3e0e15710c81908d8ea4fc007197d2 completed June 26, 2026, 5:28 a.m.
Created at: April 18, 2026, 2:20 a.m.