Triple

T594551
Position Surface form Disambiguated ID Type / Status
Subject Northern Norway E17350 entity
Predicate majorCity P316 FINISHED
Object Harstad
Harstad is a coastal town and municipality in Troms county, known as an important regional center in Northern Norway with a strong maritime and cultural heritage.
 E78588 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: Harstad | Statement: [Northern Norway, majorCity, Harstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Harstad
Context triple: [Northern Norway, majorCity, Harstad]
  • 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. Haugesund
    Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
  • C. Bodø
    Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
  • D. Fredrikstad
    Fredrikstad is a coastal city in southeastern Norway known for its well-preserved fortified old town and role as a regional educational and commercial center.
  • E. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • 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: Harstad
Triple: [Northern Norway, majorCity, Harstad]
Generated description
Harstad is a coastal town and municipality in Troms county, known as an important regional center in Northern Norway with a strong maritime and cultural heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Harstad
Target entity description: Harstad is a coastal town and municipality in Troms county, known as an important regional center in Northern Norway with a strong maritime and cultural heritage.
  • 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. Haugesund
    Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
  • C. Bodø
    Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
  • D. Fredrikstad
    Fredrikstad is a coastal city in southeastern Norway known for its well-preserved fortified old town and role as a regional educational and commercial center.
  • E. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • 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_69a49379d09c8190ac7e00b24e2810b1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49bd15c5881909b59ed4c88687e7b completed March 1, 2026, 8:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69a56930dfd88190a991adafc406c5ac completed March 2, 2026, 10:40 a.m.
NEDg Description generation batch_69a569bac3f8819083b153b73caf31c2 completed March 2, 2026, 10:43 a.m.
NED2 Entity disambiguation (via description) batch_69a56a51e1fc8190aa00945fff740927 completed March 2, 2026, 10:45 a.m.
Created at: March 1, 2026, 7:33 p.m.