Triple

T256051
Position Surface form Disambiguated ID Type / Status
Subject Battle of Narvik E5439 entity
Predicate location P40 FINISHED
Object Narvik
Narvik is a port town in northern Norway known for its strategic importance during World War II and as the site of major naval and land battles.
 E33599 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: Narvik | Statement: [Battle of Narvik, location, Narvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Narvik
Context triple: [Battle of Narvik, location, Narvik]
  • A. Arendal
    Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
  • B. Lillehammer
    Lillehammer is a Norwegian town in the Gudbrandsdalen valley, best known internationally for staging the 1994 Winter Olympics.
  • C. Gaustad
    Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
  • D. Tøyen
    Tøyen is a neighborhood in Oslo, Norway, known for its cultural institutions, parks, and educational facilities.
  • E. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • 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: Narvik
Triple: [Battle of Narvik, location, Narvik]
Generated description
Narvik is a port town in northern Norway known for its strategic importance during World War II and as the site of major naval and land battles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Narvik
Target entity description: Narvik is a port town in northern Norway known for its strategic importance during World War II and as the site of major naval and land battles.
  • A. Arendal
    Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
  • B. Lillehammer
    Lillehammer is a Norwegian town in the Gudbrandsdalen valley, best known internationally for staging the 1994 Winter Olympics.
  • C. Gaustad
    Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
  • D. Tøyen
    Tøyen is a neighborhood in Oslo, Norway, known for its cultural institutions, parks, and educational facilities.
  • E. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d5669008190978bbd7308be11f7 completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3837479408190bb6e6f0eb6a7fe46 completed March 1, 2026, 12:08 a.m.
NEDg Description generation batch_69a384140aec8190ab918512cf088464 completed March 1, 2026, 12:11 a.m.
NED2 Entity disambiguation (via description) batch_69a3848c0ed08190acf0d0e33ca8b41c completed March 1, 2026, 12:13 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.