Triple

T3593330
Position Surface form Disambiguated ID Type / Status
Subject Hjørundfjord E76077 entity
Predicate hasVillageOnShore P4011 FINISHED
Object Øye
Øye is a small Norwegian village in the Sunnmøre region, known for its dramatic fjord landscape and the historic Hotel Union Øye.
E393086 NE FINISHED

How this triple was built (4 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: Øye | Statement: [Hjørundfjord, hasVillageOnShore, Øye]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Øye
Context triple: [Hjørundfjord, hasVillageOnShore, Øye]
  • A. Andøya
    Andøya is a large Norwegian island in Nordland county, known for its dramatic coastal landscapes, space center, and rich bird and whale-watching opportunities.
  • B. Edgeøya
    Edgeøya is one of the large, remote islands in the Svalbard archipelago of Arctic Norway, known for its rugged tundra landscape and rich polar wildlife.
  • C. Finnøy
    Finnøy is a small island municipality in Rogaland county, Norway, known as the rural birthplace of mathematician Niels Henrik Abel.
  • D. Flakstadøya
    Flakstadøya is a scenic island in Norway’s Lofoten archipelago, known for its dramatic mountains, fishing villages, and coastal landscapes.
  • E. Rennesøy
    Rennesøy is an island and former municipality in Rogaland county, southwestern Norway, known for its coastal landscape and proximity to the city of Stavanger.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Øye
Triple: [Hjørundfjord, hasVillageOnShore, Øye]
Generated description
Øye is a small Norwegian village in the Sunnmøre region, known for its dramatic fjord landscape and the historic Hotel Union Øye.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Øye
Target entity description: Øye is a small Norwegian village in the Sunnmøre region, known for its dramatic fjord landscape and the historic Hotel Union Øye.
  • A. Andøya
    Andøya is a large Norwegian island in Nordland county, known for its dramatic coastal landscapes, space center, and rich bird and whale-watching opportunities.
  • B. Edgeøya
    Edgeøya is one of the large, remote islands in the Svalbard archipelago of Arctic Norway, known for its rugged tundra landscape and rich polar wildlife.
  • C. Finnøy
    Finnøy is a small island municipality in Rogaland county, Norway, known as the rural birthplace of mathematician Niels Henrik Abel.
  • D. Flakstadøya
    Flakstadøya is a scenic island in Norway’s Lofoten archipelago, known for its dramatic mountains, fishing villages, and coastal landscapes.
  • E. Rennesøy
    Rennesøy is an island and former municipality in Rogaland county, southwestern Norway, known for its coastal landscape and proximity to the city of Stavanger.
  • F. None of above. chosen

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_69ad85d8042081908af94a04c410dec0 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc15bbbcc81908d6cf95f8e70c6ca completed March 8, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503dbed588190abe9ca45b1ff68f8 completed March 14, 2026, 6:44 a.m.
NEDg Description generation batch_69b507a2a1bc819080843ed3cbb132cb completed March 14, 2026, 7 a.m.
NED2 Entity disambiguation (via description) batch_69b5090e87d881908c2e84f4a6402113 completed March 14, 2026, 7:06 a.m.
Created at: March 8, 2026, 3:22 p.m.