Triple

T23990223
Position Surface form Disambiguated ID Type / Status
Subject Monkland, Ontario E605041 entity
Predicate locatedIn P40 FINISHED
Object North Glengarry, Ontario
North Glengarry, Ontario is a rural township in eastern Ontario known for its small communities, agricultural landscape, and historic Scottish heritage.
E1618269 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: North Glengarry, Ontario | Statement: [Monkland, Ontario, locatedIn, North Glengarry, Ontario]
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: North Glengarry, Ontario
Triple: [Monkland, Ontario, locatedIn, North Glengarry, Ontario]
Generated description
North Glengarry, Ontario is a rural township in eastern Ontario known for its small communities, agricultural landscape, and historic Scottish heritage.

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_69e295463f7c8190b1c19dbd114641b9 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d38b37648190afb003cded3a7484 completed April 29, 2026, 9:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f964575c08190836bc305f347b38a completed May 21, 2026, 11:33 p.m.
NEDg Description generation batch_6a0f973823ac819092f241755fe86bf2 completed May 21, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_6a0f981441b08190a0076042748d92ea completed May 21, 2026, 11:41 p.m.
Created at: April 17, 2026, 9:37 p.m.