Triple

T21545419
Position Surface form Disambiguated ID Type / Status
Subject Oslomarka E531610 entity
Predicate hasPart P35 FINISHED
Object Gjelleråsen
Gjelleråsen is a forested hill and recreational area on the outskirts of Oslo, Norway, known for outdoor activities such as hiking and skiing.
 E1496496 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: Gjelleråsen | Statement: [Oslomarka, hasPart, Gjelleråsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gjelleråsen
Context triple: [Oslomarka, hasPart, Gjelleråsen]
  • A. Glåma
    Glåma is the longest and largest river in Norway, flowing through eastern parts of the country before emptying into the Oslofjord.
  • B. Skogsvåg
    Skogsvåg is a small coastal village in western Norway, located on the island of Sotra in Vestland county.
  • C. Gjesåsen
    Gjesåsen is a small rural village in Åsnes Municipality in Innlandet county, Norway, known for its agricultural surroundings and proximity to the local center of Flisa.
  • D. Ullernåsen
    Ullernåsen is a residential hillside neighborhood in Oslo, Norway, known for its apartment blocks, green surroundings, and views over the western parts of the city.
  • E. Skøyenåsen
    Skøyenåsen is a residential neighborhood in Oslo, Norway, known for its green surroundings and access to public transportation.
  • 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: Gjelleråsen
Triple: [Oslomarka, hasPart, Gjelleråsen]
Generated description
Gjelleråsen is a forested hill and recreational area on the outskirts of Oslo, Norway, known for outdoor activities such as hiking and skiing.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gjelleråsen
Target entity description: Gjelleråsen is a forested hill and recreational area on the outskirts of Oslo, Norway, known for outdoor activities such as hiking and skiing.
  • A. Glåma
    Glåma is the longest and largest river in Norway, flowing through eastern parts of the country before emptying into the Oslofjord.
  • B. Skogsvåg
    Skogsvåg is a small coastal village in western Norway, located on the island of Sotra in Vestland county.
  • C. Gjesåsen
    Gjesåsen is a small rural village in Åsnes Municipality in Innlandet county, Norway, known for its agricultural surroundings and proximity to the local center of Flisa.
  • D. Ullernåsen
    Ullernåsen is a residential hillside neighborhood in Oslo, Norway, known for its apartment blocks, green surroundings, and views over the western parts of the city.
  • E. Skøyenåsen
    Skøyenåsen is a residential neighborhood in Oslo, Norway, known for its green surroundings and access to public transportation.
  • 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_69e0c45f17148190949c330ab9c27706 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeb58e38808190888f3501cf4fff7c completed April 27, 2026, 1:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0a1e04258c819098f7254a63a7c0c3 completed May 17, 2026, 7:59 p.m.
NEDg Description generation batch_6a0a1eac9b648190881c97d474762fc0 completed May 17, 2026, 8:01 p.m.
NED2 Entity disambiguation (via description) batch_6a0a1f3b77488190bfb73b9e83446bb3 completed May 17, 2026, 8:04 p.m.
Created at: April 16, 2026, 6:28 p.m.