Triple

T23741336
Position Surface form Disambiguated ID Type / Status
Subject Jarawan Bantu languages E586679 entity
Predicate areAssociatedWith P629 FINISHED
Object Jarawan peoples
The Jarawan peoples are a group of ethnic communities in parts of Nigeria and Cameroon known for speaking Jarawan Bantu languages and maintaining distinct cultural traditions.
E1599196 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: Jarawan peoples | Statement: [Jarawan Bantu languages, areAssociatedWith, Jarawan peoples]
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: Jarawan peoples
Triple: [Jarawan Bantu languages, areAssociatedWith, Jarawan peoples]
Generated description
The Jarawan peoples are a group of ethnic communities in parts of Nigeria and Cameroon known for speaking Jarawan Bantu languages and maintaining distinct cultural traditions.

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_69e24908efb08190bf755c3a9b91f222 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bad61d908190a0a8493bbba95d49 completed April 29, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53cd53bc819083234646e30707f5 completed May 21, 2026, 6:49 p.m.
NEDg Description generation batch_6a0f5558f50c8190a268fbcde798512e completed May 21, 2026, 6:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0f56691aa08190b46a9ad2c3dce1d0 completed May 21, 2026, 7 p.m.
Created at: April 17, 2026, 7:11 p.m.