Triple

T5790634
Position Surface form Disambiguated ID Type / Status
Subject Gamle Oslo E128382 entity
Predicate containsNeighbourhood P4813 FINISHED
Object Etterstad
Etterstad is a residential neighborhood in Oslo, Norway, known for its apartment blocks, green areas, and proximity to the city center.
E547412 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: Etterstad | Statement: [Gamle Oslo, containsNeighbourhood, Etterstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Etterstad
Context triple: [Gamle Oslo, containsNeighbourhood, Etterstad]
  • A. Gaustad
    Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
  • B. Stordal
    Stordal is a small village and former municipality in western Norway, known for its scenic fjord landscape and traditional Norwegian architecture.
  • C. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • D. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • E. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • 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: Etterstad
Triple: [Gamle Oslo, containsNeighbourhood, Etterstad]
Generated description
Etterstad is a residential neighborhood in Oslo, Norway, known for its apartment blocks, green areas, and proximity to the city center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Etterstad
Target entity description: Etterstad is a residential neighborhood in Oslo, Norway, known for its apartment blocks, green areas, and proximity to the city center.
  • A. Gaustad
    Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
  • B. Stordal
    Stordal is a small village and former municipality in western Norway, known for its scenic fjord landscape and traditional Norwegian architecture.
  • C. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • D. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • E. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • 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_69c00845ca68819081a2ce3ecca577f7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a5585788190821b8da40259e0e7 completed March 22, 2026, 5:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09820f5c08190811e848eb44ce5b9 completed March 23, 2026, 1:32 a.m.
NEDg Description generation batch_69c0990bf38081908c09c5dfe660c35b completed March 23, 2026, 1:36 a.m.
NED2 Entity disambiguation (via description) batch_69c099b4bc4481909e7cf6886e5ccbea completed March 23, 2026, 1:39 a.m.
Created at: March 22, 2026, 3:51 p.m.