Triple

T33059901
Position Surface form Disambiguated ID Type / Status
Subject Collège de la Sagesse E845943 entity
Predicate networkMembership P10 FINISHED
Object Sagesse schools network
The Sagesse schools network is an educational organization that unites various Sagesse-branded institutions, such as Collège de la Sagesse, under a common academic and administrative framework.
 E845943 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: Sagesse schools network | Statement: [Collège de la Sagesse, networkMembership, Sagesse schools network]
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: Sagesse schools network
Triple: [Collège de la Sagesse, networkMembership, Sagesse schools network]
Generated description
The Sagesse schools network is an educational organization that unites various Sagesse-branded institutions, such as Collège de la Sagesse, under a common academic and administrative framework.

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_69f3495333b8819095e9af56855b9061 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d37919f08190bb7ff7500a689447 completed May 3, 2026, 4:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34e521fd548190b189ddde2402a938 completed June 19, 2026, 6:43 a.m.
NEDg Description generation batch_6a34e5f9f52c8190920d2db26c801c7f completed June 19, 2026, 6:47 a.m.
NED2 Entity disambiguation (via description) batch_6a34e82ab0b48190b73217391c4e9d64 completed June 19, 2026, 6:56 a.m.
Created at: May 1, 2026, 1:25 a.m.