Triple

T28550626
Position Surface form Disambiguated ID Type / Status
Subject Scott Moir E722875 entity
Predicate residence P75 FINISHED
Object Ilderton, Ontario, Canada
Ilderton, Ontario, Canada is a small rural community near London, Ontario, best known for its close-knit atmosphere and as the hometown of Olympic ice dancer Scott Moir.
E1822039 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: Ilderton, Ontario, Canada | Statement: [Scott Moir, residence, Ilderton, Ontario, Canada]
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: Ilderton, Ontario, Canada
Triple: [Scott Moir, residence, Ilderton, Ontario, Canada]
Generated description
Ilderton, Ontario, Canada is a small rural community near London, Ontario, best known for its close-knit atmosphere and as the hometown of Olympic ice dancer Scott Moir.

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_69f01a60204481909af1bb76247b8221 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f65010b7588190a38981fc7c925ed3 completed May 2, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac6dd068819088eab5fd18c6df1e completed May 31, 2026, 9:47 p.m.
NEDg Description generation batch_6a1cad2176088190b0a526811f5c0016 completed May 31, 2026, 9:50 p.m.
NED2 Entity disambiguation (via description) batch_6a1cadf50e1c81908235678a32385afb completed May 31, 2026, 9:53 p.m.
Created at: April 28, 2026, 3:42 a.m.