Triple

T26899803
Position Surface form Disambiguated ID Type / Status
Subject Longueuil–Université-de-Sherbrooke station E677995 entity
Predicate servesInstitution P8369 FINISHED
Object Collège Édouard-Montpetit
Collège Édouard-Montpetit is a French-language public college (CEGEP) located in Longueuil, Quebec, offering pre-university and technical programs.
E1752572 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: Collège Édouard-Montpetit | Statement: [Longueuil–Université-de-Sherbrooke station, servesInstitution, Collège Édouard-Montpetit]
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: Collège Édouard-Montpetit
Triple: [Longueuil–Université-de-Sherbrooke station, servesInstitution, Collège Édouard-Montpetit]
Generated description
Collège Édouard-Montpetit is a French-language public college (CEGEP) located in Longueuil, Quebec, offering pre-university and technical programs.

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_69eee9befee48190a26f214faa867be7 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61fae0fc48190a9099a1e3d705a90 completed May 2, 2026, 4 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12298e3ee4819082182b6e9864d13f completed May 23, 2026, 10:26 p.m.
NEDg Description generation batch_6a122ab3c688819090346bce8a20c061 completed May 23, 2026, 10:31 p.m.
NED2 Entity disambiguation (via description) batch_6a122bf0a15c81909e479281bb9e7d73 completed May 23, 2026, 10:36 p.m.
Created at: April 27, 2026, 5:50 a.m.