Triple

T29175543
Position Surface form Disambiguated ID Type / Status
Subject Voss mountains E739597 entity
Predicate near P350 FINISHED
Object Sognefjord region
The Sognefjord region is a scenic area in western Norway centered around the country’s longest and deepest fjord, known for its dramatic mountains, waterfalls, and traditional fjord villages.
E1861368 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: Sognefjord region | Statement: [Voss mountains, near, Sognefjord 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: Sognefjord region
Triple: [Voss mountains, near, Sognefjord region]
Generated description
The Sognefjord region is a scenic area in western Norway centered around the country’s longest and deepest fjord, known for its dramatic mountains, waterfalls, and traditional fjord villages.

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_69f07cb6394c8190ab7842c48e699e2a completed April 28, 2026, 9:24 a.m.
NER Named-entity recognition batch_69f663403c048190ae61c2a304e59d5a completed May 2, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25a843d954819083715f7fda242908 completed June 7, 2026, 5:20 p.m.
NEDg Description generation batch_6a25ac482b2c8190b29f490879ef6ea6 completed June 7, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_6a25b03453348190952e1ebd49c800b9 completed June 7, 2026, 5:53 p.m.
Created at: April 28, 2026, 11:54 a.m.