Triple

T22511814
Position Surface form Disambiguated ID Type / Status
Subject Lakefield College School E556537 entity
Predicate locatedNear P294 FINISHED
Object Lakefield Lake
Lakefield Lake is a freshwater lake in Ontario, Canada, known for its scenic setting and recreational use, particularly by the nearby Lakefield College School community.
E2293622 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: Lakefield Lake | Statement: [Lakefield College School, locatedNear, Lakefield Lake]
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: Lakefield Lake
Triple: [Lakefield College School, locatedNear, Lakefield Lake]
Generated description
Lakefield Lake is a freshwater lake in Ontario, Canada, known for its scenic setting and recreational use, particularly by the nearby Lakefield College School community.

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_69e11e555edc81909ca803587dafd747 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15d61a27881909faed490d2b65f39 completed April 29, 2026, 1:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7ae31333f0819084fe3f90d791cc5d completed Aug. 11, 2026, 8:53 a.m.
NEDg Description generation batch_6a7ae3cd15048190bbb57c91017fa1fe completed Aug. 11, 2026, 8:56 a.m.
NED2 Entity disambiguation (via description) batch_6a7ae6e27904819098de737b79c32d1b completed Aug. 11, 2026, 9:09 a.m.
Created at: April 16, 2026, 8:50 p.m.