Triple

T33838689
Position Surface form Disambiguated ID Type / Status
Subject African New Zealanders E867302 entity
Predicate relatedGroup P37 FINISHED
Object African Australians
African Australians are Australian residents and citizens of African ancestry, encompassing both recent migrants and their descendants from diverse African countries and cultures.
E2070053 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: African Australians | Statement: [African New Zealanders, relatedGroup, African Australians]
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: African Australians
Triple: [African New Zealanders, relatedGroup, African Australians]
Generated description
African Australians are Australian residents and citizens of African ancestry, encompassing both recent migrants and their descendants from diverse African countries and cultures.

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_69f34992ad40819087760ed939bd2a7a completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7004d97408190a3b09fa2bda3d42e completed May 3, 2026, 7:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a366ead654c8190abe9721f483eacfd completed June 20, 2026, 10:42 a.m.
NEDg Description generation batch_6a366f86630c81908530464a68656b76 completed June 20, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a3671039b748190a4dd9ccda7446e01 completed June 20, 2026, 10:52 a.m.
Created at: May 1, 2026, 1:47 a.m.