Triple

T25171897
Position Surface form Disambiguated ID Type / Status
Subject Ontario school boards E630342 entity
Predicate hasType P0 FINISHED
Object English Catholic school board
An English Catholic school board is a publicly funded educational authority in Ontario that administers English-language schools providing education grounded in the Roman Catholic faith.
E1668788 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: English Catholic school board | Statement: [Ontario school boards, hasType, English Catholic school board]
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: English Catholic school board
Triple: [Ontario school boards, hasType, English Catholic school board]
Generated description
An English Catholic school board is a publicly funded educational authority in Ontario that administers English-language schools providing education grounded in the Roman Catholic faith.

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_69e75a87c9b88190ab60731902a99750 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f46d47886c81908507ce1d55e5643c completed May 1, 2026, 9:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105d17bb8c8190988ddd0e08da5ab3 completed May 22, 2026, 1:41 p.m.
NEDg Description generation batch_6a105f7fdd6081909dba228f0e160acd completed May 22, 2026, 1:52 p.m.
NED2 Entity disambiguation (via description) batch_6a105ffdbf2c8190a55bd26536db8248 completed May 22, 2026, 1:54 p.m.
Created at: April 21, 2026, 12:20 p.m.