Triple

T35451077
Position Surface form Disambiguated ID Type / Status
Subject Norwegian Scenic Routes E1024626 entity
Predicate includesRoute P4374 FINISHED
Object Havøysund
Havøysund is a remote coastal village in northern Norway known for its dramatic Arctic landscapes and role as a gateway to scenic routes and fishing grounds along the Barents Sea.
E2162455 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: Havøysund | Statement: [Norwegian Scenic Routes, includesRoute, Havøysund]
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: Havøysund
Triple: [Norwegian Scenic Routes, includesRoute, Havøysund]
Generated description
Havøysund is a remote coastal village in northern Norway known for its dramatic Arctic landscapes and role as a gateway to scenic routes and fishing grounds along the Barents Sea.

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_69f76df92f108190817222e520e22268 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f796296e1881908d001cad8fbb7b1b completed May 3, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38b6e085f881909971e4d083ebe8d8 completed June 22, 2026, 4:15 a.m.
NEDg Description generation batch_6a38b773d0288190810c55e95f7aa097 completed June 22, 2026, 4:17 a.m.
NED2 Entity disambiguation (via description) batch_6a38b7f01ad48190b26328f1cb7d578f completed June 22, 2026, 4:20 a.m.
Created at: May 3, 2026, 4:04 p.m.