Triple

T26193243
Position Surface form Disambiguated ID Type / Status
Subject Highgate Springs, Vermont E655023 entity
Predicate borderCrossingTo P4105 FINISHED
Object Saint-Armand, Quebec
Saint-Armand, Quebec is a small rural municipality in the Estrie region of southern Quebec, Canada, located along the U.S. border opposite Vermont.
E1730284 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: Saint-Armand, Quebec | Statement: [Highgate Springs, Vermont, borderCrossingTo, Saint-Armand, Quebec]
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: Saint-Armand, Quebec
Triple: [Highgate Springs, Vermont, borderCrossingTo, Saint-Armand, Quebec]
Generated description
Saint-Armand, Quebec is a small rural municipality in the Estrie region of southern Quebec, Canada, located along the U.S. border opposite Vermont.

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_69ee5b48236c81908fe385b6afc4f60b completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60ca4397481908a10249146f7c5ef completed May 2, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c7ef5adc81909980f40f754058ad completed May 23, 2026, 3:29 p.m.
NEDg Description generation batch_6a11c8a47010819088d45a3fe9c84cd5 completed May 23, 2026, 3:32 p.m.
NED2 Entity disambiguation (via description) batch_6a11c9206c588190a43338df1f2e4d88 completed May 23, 2026, 3:34 p.m.
Created at: April 26, 2026, 8:45 p.m.