Triple

T26513981
Position Surface form Disambiguated ID Type / Status
Subject Appalachian region of Quebec E669761 entity
Predicate hasSubregion P285 FINISHED
Object Notre Dame Mountains
The Notre Dame Mountains are a range of low, ancient mountains in eastern Quebec that form part of the northern Appalachian chain and are known for their forested landscapes and rolling terrain.
E1770718 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: Notre Dame Mountains | Statement: [Appalachian region of Quebec, hasSubregion, Notre Dame Mountains]
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: Notre Dame Mountains
Triple: [Appalachian region of Quebec, hasSubregion, Notre Dame Mountains]
Generated description
The Notre Dame Mountains are a range of low, ancient mountains in eastern Quebec that form part of the northern Appalachian chain and are known for their forested landscapes and rolling terrain.

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_69eeb31b6dcc8190b30632dc3928a0c0 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f61394b50c81909e628b2e5b1aa3d5 completed May 2, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12a7ac21e88190aade974b2b14c514 completed May 24, 2026, 7:24 a.m.
NEDg Description generation batch_6a12a9369fb081909cf7728dcb943585 completed May 24, 2026, 7:31 a.m.
NED2 Entity disambiguation (via description) batch_6a12aa0e55a88190ae8b69a3063f47a7 completed May 24, 2026, 7:34 a.m.
Created at: April 27, 2026, 1:22 a.m.