Triple

T34711092
Position Surface form Disambiguated ID Type / Status
Subject Ranier, Minnesota E1000646 entity
Predicate region P40 FINISHED
Object Border Lakes region
The Border Lakes region is a scenic area of interconnected lakes and forests along the U.S.–Canada border in northern Minnesota and Ontario, known for wilderness recreation and canoeing.
E2108231 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: Border Lakes region | Statement: [Ranier, Minnesota, region, Border Lakes region]
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: Border Lakes region
Triple: [Ranier, Minnesota, region, Border Lakes region]
Generated description
The Border Lakes region is a scenic area of interconnected lakes and forests along the U.S.–Canada border in northern Minnesota and Ontario, known for wilderness recreation and canoeing.

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_69f76dad3f108190a280fd0a2f4ee89a completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77989178881909103cc14f4365eec completed May 3, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37530d349881909fa809e61698e44a completed June 21, 2026, 2:57 a.m.
NEDg Description generation batch_6a3753a027888190b9458f35c96cfe80 completed June 21, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_6a37541fa8d48190aef474f094893f32 completed June 21, 2026, 3:01 a.m.
Created at: May 3, 2026, 3:59 p.m.