Triple

T24836059
Position Surface form Disambiguated ID Type / Status
Subject Trinity College School E621476 entity
Predicate foundedBy P104 FINISHED
Object William Arthur Johnson
William Arthur Johnson was a 19th-century Anglican clergyman and educator best known for establishing one of Canada's oldest independent schools, Trinity College School.
E1953011 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: William Arthur Johnson | Statement: [Trinity College School, foundedBy, William Arthur Johnson]
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: William Arthur Johnson
Triple: [Trinity College School, foundedBy, William Arthur Johnson]
Generated description
William Arthur Johnson was a 19th-century Anglican clergyman and educator best known for establishing one of Canada's oldest independent schools, Trinity College School.

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_69e2fac185d48190a0a6073ad1f6b792 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f422b7642c8190aed5133e6275e8a4 completed May 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a296bb237248190bbf989dbc0d9c9be completed June 10, 2026, 1:50 p.m.
NEDg Description generation batch_6a296e216798819083cbb35303b0c0f5 completed June 10, 2026, 2:01 p.m.
NED2 Entity disambiguation (via description) batch_6a299bd98c608190971bff14a9497cd5 completed June 10, 2026, 5:16 p.m.
Created at: April 18, 2026, 5:17 a.m.