Triple

T33873938
Position Surface form Disambiguated ID Type / Status
Subject Liyana (band) E868302 entity
Predicate associatedWith P37 FINISHED
Object King George VI School
King George VI School is a Zimbabwean educational institution known for its strong support of the deaf community and for nurturing the acclaimed all-deaf band Liyana.
E2074100 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: King George VI School | Statement: [Liyana (band), associatedWith, King George VI School]
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: King George VI School
Triple: [Liyana (band), associatedWith, King George VI School]
Generated description
King George VI School is a Zimbabwean educational institution known for its strong support of the deaf community and for nurturing the acclaimed all-deaf band Liyana.

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_69f34995029081909ede0f7df73d1a5e completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f701042bd081908bf58d12468987b6 completed May 3, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3682362e5881908ab8a4cd17e748e9 completed June 20, 2026, 12:06 p.m.
NEDg Description generation batch_6a3683e1fa748190991b876a33e60729 completed June 20, 2026, 12:13 p.m.
NED2 Entity disambiguation (via description) batch_6a3684bb5d7c81909a4e397d824d7d32 completed June 20, 2026, 12:16 p.m.
Created at: May 1, 2026, 1:47 a.m.