Triple

T5098166
Position Surface form Disambiguated ID Type / Status
Subject Fosen E114916 entity
Predicate contains P35 FINISHED
Object Ørland
Ørland is a coastal municipality in Trøndelag county, Norway, known for its strategic air base and rich maritime and agricultural landscape.
E506032 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: Ørland | Statement: [Fosen, contains, Ørland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ørland
Context triple: [Fosen, contains, Ørland]
  • A. Ørje
    Ørje is a small village in southeastern Norway known for its historic locks on the Halden Canal and its role as a local commercial and service hub.
  • B. Røst
    Røst is a small, remote island and fishing community in northern Norway, known for its dramatic coastal scenery, rich seabird colonies, and traditional cod fisheries.
  • C. Nøtterøy
    Nøtterøy is a large, populated island and former municipality in Vestfold, Norway, situated in the Oslofjord and known for its coastal landscapes and residential communities.
  • D. 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.
  • E. Øksnes
    Øksnes is a coastal municipality in Nordland county, Norway, known for its fishing communities and location within the Vesterålen archipelago.
  • 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: Ørland
Triple: [Fosen, contains, Ørland]
Generated description
Ørland is a coastal municipality in Trøndelag county, Norway, known for its strategic air base and rich maritime and agricultural landscape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ørland
Target entity description: Ørland is a coastal municipality in Trøndelag county, Norway, known for its strategic air base and rich maritime and agricultural landscape.
  • A. Ørje
    Ørje is a small village in southeastern Norway known for its historic locks on the Halden Canal and its role as a local commercial and service hub.
  • B. Røst
    Røst is a small, remote island and fishing community in northern Norway, known for its dramatic coastal scenery, rich seabird colonies, and traditional cod fisheries.
  • C. Nøtterøy
    Nøtterøy is a large, populated island and former municipality in Vestfold, Norway, situated in the Oslofjord and known for its coastal landscapes and residential communities.
  • D. 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.
  • E. Øksnes
    Øksnes is a coastal municipality in Nordland county, Norway, known for its fishing communities and location within the Vesterålen archipelago.
  • 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_69bd443fc49c819089629c00e311310c completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7567d21081909227ed8f08b74c71 completed March 20, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe4e829c819092acbc078e552d75 completed March 21, 2026, 8:23 p.m.
NEDg Description generation batch_69befefc89fc819092078e51fcd5db6b completed March 21, 2026, 8:26 p.m.
NED2 Entity disambiguation (via description) batch_69beff5866dc81909bb2201e78b8b30b completed March 21, 2026, 8:28 p.m.
Created at: March 20, 2026, 1:40 p.m.