Triple

T34126445
Position Surface form Disambiguated ID Type / Status
Subject Oslo (maritime border) E875290 entity
Predicate adjacentTo P224 FINISHED
Object Nesodden coastline
The Nesodden coastline is a scenic stretch of shoreline on the Nesodden peninsula in the Oslofjord, known for its views toward Oslo and its mix of residential areas, beaches, and natural landscapes.
E2083109 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: Nesodden coastline | Statement: [Oslo (maritime border), adjacentTo, Nesodden coastline]
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: Nesodden coastline
Triple: [Oslo (maritime border), adjacentTo, Nesodden coastline]
Generated description
The Nesodden coastline is a scenic stretch of shoreline on the Nesodden peninsula in the Oslofjord, known for its views toward Oslo and its mix of residential areas, beaches, and natural landscapes.

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_69f349aa33848190a2e6c5e4533c8444 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70f49df788190bc397882cd5f6be4 completed May 3, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36b77796288190b12f758841e70b9b completed June 20, 2026, 3:53 p.m.
NEDg Description generation batch_6a36b898418c81909c6d0af53affd7e1 completed June 20, 2026, 3:58 p.m.
NED2 Entity disambiguation (via description) batch_6a36b989a6d081908c6873c7dc63cc99 completed June 20, 2026, 4:02 p.m.
Created at: May 1, 2026, 1:53 a.m.